Cybersecurity in Consumer Adoption of Smart Home …...The literature on the current and future...

Cybersecurity in Consumer Adoption of SmartHome Technology

byRaed Iskandar

Supervised by Professor Mika Westerlund

A thesis submitted to the Faculty of Graduate andPostdoctoral Affairs in fulfillment of the requirements for the

degree in

Masters of Applied Sciencein

Technology Innovation Management

Summer 2017

Carleton UniversityOttawa, Ontario

Copyright c© 2017 Raed Iskandar

Cybersecurity in Consumer Adoption of Smart Home Technology Raed Iskandar

Abstract

The highly anticipated smart home technology for everyday

life has been growing over the past quarter century. Using stan-

dard technology adoption models, previous research produced

conflicting results that did not reflect the market accurately.

Amongst the indicated challenges for the future of smart home

technology is the commonly overlooked barrier cybersecurity.

To better understand the market’s expectation we conducted

consumer interviews that produced a modified model for smart

home adoption in the Canadian market. The resulting adapted

model proposes a link between cybersecurity and the behavioral

intent of potential consumers. Components of the cybersecurity

determinant are identified as trust, safety, and privacy which

are moderated by the consumer’s level of technical knowledge.

Implications of our findings could improve the performance of

smart home technology in the market and inspire the creation

of innovative solutions that increase the security of the IoT in-

dustry.

I


Glossary

• Cybersecurity: the organization and collection of resources,

processes, and structures used to protect cyberspace and

cyberspace-enabled systems from occurrences that misalign

de jure from de facto property rights.

• Internet of Things (IoT): a dynamic global network infras-

tructure with self configuring capabilities based on standard

and interoperable communication protocols where physi-

cal and virtual “things” have identities, physical attributes,

and virtual personalities, use intelligent interfaces, and are

seamlessly integrated into the information network.

• Smart Homes: a residence equipped with computing and

information technology which anticipates and responds to

the needs of the occupants, working to promote their com-

fort, convenience, security, and entertainment through the

management of technology within the home and connec-

tions to the world beyond.

II


Contents

ABSTRACT I

TABLE OF CONTENTS III

ACKNOWLEDGEMENT VIII

1 INTRODUCTION 1

1.1 OBJECTIVE . . . . . . . . . . . . . . . . . . . . . . . . 4

1.2 DELIVERABLES . . . . . . . . . . . . . . . . . . . . . . 4

1.3 DELIMITATIONS . . . . . . . . . . . . . . . . . . . . . 4

1.4 RELEVANCE AND VALUE OF DELIVERABLES . . . 5

1.5 METHODOLOGY . . . . . . . . . . . . . . . . . . . . . 6

1.6 ORGANIZATION OF THE THESIS . . . . . . . . . . . 7

2 LITERATURE REVIEW 8

2.1 TECHNOLOGY ADOPTION MODELS . . . . . . . . . 8

2.2 BOUNDARIES OF SMART HOMES . . . . . . . . . . . 16

2.3 CYBERSECURITY AND CHALLENGES IN CONNECTED

TECHNOLOGY . . . . . . . . . . . . . . . . . . . . . . 20

2.3.1 Human interaction Challenges . . . . . . . . . . . 20

2.3.2 Social Barriers . . . . . . . . . . . . . . . . . . . 21

2.3.3 Cybersecurity issues . . . . . . . . . . . . . . . . 22

2.4 SUMMARY AND KEY FINDINGS . . . . . . . . . . . . 28

III


3 RESEARCH DESIGN AND METHODOLOGY 31

3.1 OVERVIEW . . . . . . . . . . . . . . . . . . . . . . . . . 31

3.2 METHODS AND INSTRUMENTS . . . . . . . . . . . . 34

3.3 DETAILS OF DATA COLLECTION . . . . . . . . . . . 38

3.4 PARTICIPANTS . . . . . . . . . . . . . . . . . . . . . . 40

3.5 IMPORTANCE AND LIMITATION . . . . . . . . . . . 41

4 RESULTS 42

4.1 OVERVIEW . . . . . . . . . . . . . . . . . . . . . . . . . 42

4.2 CONSUMER AWARENESS OF SMART HOMES . . . . 46

4.3 CYBERSECURITY PREDISPOSITION . . . . . . . . . 47

4.4 INDEPTH EXAMINATION OF RESULTS . . . . . . . 48

4.4.1 DEPTH OF TECHNICAL KNOWLEDGE . . . . 48

4.4.2 DEFINITION OF SMART HOME TECHNOL-

OGY . . . . . . . . . . . . . . . . . . . . . . . . . 53

4.4.3 WILLINGNESS TO OWN SMART HOME TECH-

NOLOGY . . . . . . . . . . . . . . . . . . . . . . 55

4.4.4 WHAT ARE THE KEY FACTORS AND CON-

CERNS . . . . . . . . . . . . . . . . . . . . . . . 58

4.4.5 TECHNOLOGY SECTOR . . . . . . . . . . . . . 64

4.4.6 FAMILIARITY TO CYBERSECURITY . . . . . 67

4.4.7 COMPONENTS OF CYBERSECURITY . . . . 74

4.4.8 RANKING THE COMPONENTS BY IMPACT

LEVELS . . . . . . . . . . . . . . . . . . . . . . . 80

5 DISCUSSION 85

IV


5.1 SUMMARY OF RESULTS . . . . . . . . . . . . . . . . . 85

5.2 INTERPRETATION OF FINDINGS . . . . . . . . . . . 91

5.3 IMPLICATIONS TO THEORY . . . . . . . . . . . . . . 97

5.4 IMPLICATIONS TO PRACTITONERS . . . . . . . . . 99

5.5 LIMITATIONS . . . . . . . . . . . . . . . . . . . . . . . 101

5.6 FUTURE RESEARCH . . . . . . . . . . . . . . . . . . . 103

6 CONCLUSION 105

7 APPENDICES 107

7.1 APPENDIX A - INTERVIEW SCRIPT . . . . . . . . . 107

8 REFERENCES 111

V


List of Figures

1 Technology Acceptance Model (Davis Jr., 1986) . . . . . 9

2 User Acceptance Model (Venkatesh et al., 2003) . . . . . 11

3 Unified Theory of Acceptance and Use of Technology

(Venkatesh et al., 2003) . . . . . . . . . . . . . . . . . . . 12

4 Unified Theory of Acceptance and Use of Technology 2

(Venkatesh et al., 2012) . . . . . . . . . . . . . . . . . . . 14

5 Preliminary Theoretical Model: Smart Home Technol-

ogy Acceptance . . . . . . . . . . . . . . . . . . . . . . . 30

6 Distribution of technical knowledge . . . . . . . . . . . . 46

7 Technology Sector Distribution . . . . . . . . . . . . . . 65

8 Familiarity to Cybersecurity . . . . . . . . . . . . . . . . 74

9 Adjusted Familiarity to Cybersecurity . . . . . . . . . . . 74

10 Cybersecurity component intensity . . . . . . . . . . . . 75

11 Revised Theoretical Model: Smart Home Technology

Acceptance . . . . . . . . . . . . . . . . . . . . . . . . . 96

VI


List of Tables

1 Literature Review Streams . . . . . . . . . . . . . . . . . 8

2 Compromise of Cybersecurity Objectives by Component 27

3 Steps of The Research Method . . . . . . . . . . . . . . . 33

4 Steps of Conducting Modified Grounded Theory Analysis 35

5 Participant Demographics . . . . . . . . . . . . . . . . . 44

6 Competencies Proficiency Scale . . . . . . . . . . . . . . 48

7 Key factors . . . . . . . . . . . . . . . . . . . . . . . . . 59

8 Cybersecurity Component Ranking Amalgamation . . . . 81

VII


ACKNOWLEDGEMENT

The completion of this thesis would not have been made possible with-

out the continuous support of my family and friends. I am indebted to

their patience and encouragement through the past year of my research.

I am grateful for the efforts of my supervisor Dr. Mika Westerlund and

his unwavering dedication in providing advice and support for the du-

ration of my studies.

VIII


1 INTRODUCTION

This research examines the role cybersecurity plays in the adoption of

smart home technology. Adoption factors have come into scrutiny over

the last decade for this product market after years of failure to reach

expected growth in sales. In 1970 information technology consultant

James Martin and Adrian R.D. Norman published a book titled The

Computerized Society, where they discussed the potential to use a com-

puter in homes to aid in day-to-day tasks. Their vision of the future

modern homes included automated control of home appliances through

networks and over the internet, with incredible resemblance to what

technology can do today and is widely considered the first introduction

of smart homes concept (Martin & Norman, 1973, P.161).

By 1989 the concept of smart homes was no longer seen as signif-

icantly revolutionary (Forester, 1989, P. 224). Soon after, magazines

such as Boys’ Life, Vanity Fair, and House Beautiful began to publish

articles about smart homes which at this point had become an appeal-

ing idea for the average home lifestyle (Aldrich, 2003). Although the

past century has been marked by incredible advances in technology,

the barriers to the smart home market have yet to be overcome. Re-

search produced by organizations such as Cisco, Gartner, and General

Electric have widely contradicting predictions of the future market for

smart homes (Cisco; Savitz, 2012; Columbus, 2016).

1


The smart home concept is constructed from multiple layers of con-

nected technological devices that operate together producing the im-

mersive experience that is smart homes. Those devices and appliances

are commonly referred to as smart or connected technologies; together

those devices form the network of Internet of Things (IoT). The term

IoT continues to evolve, with some debate as to what “Things” can be.

A conceptual framework from Vermesan et al. (2011) explains IoT as

“... a dynamic global network infrastructure with self configuring capa-

bilities based on standard and interoperable communication protocols

where physical and virtual “things” have identities, physical attributes,

and virtual personalities, use intelligent interfaces, and are seamlessly

integrated into the information network.”

The literature on the current and future state of smart homes sug-

gests that there are some critical challenges that must be addressed

(Rose, Eldridge, & Chapin, 2015; Alam et al., 2012). Key fundamen-

tal factors of smart homes have been brought under examination that

poses a question of whether the current adoption models need to be

rethought. Research suggests that the security of the IoT could be a

central part of the adoption challenge (Singh & Singh, 2015).

A recent study ran a group of IoT products from different manu-

facturers through extensive security testing and found some commonly

known issues still existed in the technology (Stanislav & Beardsley,

2015). The academic literature presents a theoretical indication to the

2


risk of cybersecurity, but case evidence is more present through the

media. The CNBC, as well as other news reporting agencies, reported

on an incident involving IoT devices that affected thousands of home

owners. Schlesinger and Day (2016) state, “In October, hackers took

over 100,000 IoT devices and used them to block traffic to well-known

websites, including Twitter and Netflix.”

The risks mentioned above use the term cybersecurity to refer to

threats affecting devices connected on a cyber-network. Craigen, Diakun-

Thibault, & Purse (2014) provided a unification for the term cybersecu-

rity that bridges amongst technical and non-technical academic streams

resulting in the following definition “Cybersecurity is the organization

and collection of resources, processes, and structures used to protect

cyberspace and cyberspace-enabled systems from occurrences that mis-

align de jure from de facto property rights.”

Understanding the growing problems facing Smart homes, we believe

now is the time to address the challenge of cybersecurity. Our research

examines this critical factor through the use of potential consumer data

to advance the technology adoption models.

In this research, we use the definition of smart homes given by Aldrich

(2003). The definition focuses on technology within a home that pro-

vides the resident with automated management of technology in their

home in response to their current needs or in anticipation of future

3


needs.

1.1 OBJECTIVE

This research aims to advance our understanding of consumer adoption

of cybersecurity features by producing a modified adoption model sup-

ported by current potential consumers of smart homes. The model will

provide a better understanding of the role that cybersecurity takes in

the customer’s purchasing decision of smart home technology. We state

the research question as: What role does Cybersecurity play in Smart

Home technology adoption by consumers in the household market.

1.2 DELIVERABLES

Readers examining this research should expect to find the following

deliverables. (1) List of key components perceived to determine the

level cybersecurity in the smart home market. (2) A conceptual tech-

nology adoption model specific to smart homes. (3) Propositions of the

relationships between the model’s adoption factors.

1.3 DELIMITATIONS

Delivering an improved understanding of the user acceptance of smart

home technology requires a methodical structure of research. Defining

our delimitations is equally important to this research as the declara-

tion of deliverables.

4


The study will not focus on smart home technology products that

are mandatory i.e., those that do not offer the consumer a choices for

selection, such as government regulated installations. This focus en-

sures that the data collection and findings will reflect consumer choice

adoption of the technology.

Exploration of adoption will focus on the individual household con-

sumers, avoiding business to business relationships. This allows us to

narrow down the factors involved in the adoption process to a smaller

set of unknown variables.

The extensive literature on technology adoption has resulted in a

widely accepted set of adoption factors which this research will not

set to disprove. A higher value is delivered through focusing on the

exploration of additional factors relevant to the adoption of smart home

technology.

1.4 RELEVANCE AND VALUE OF DELIVER-

ABLES

This research is valuable on two fronts. First, it provides relevant find-

ings for the organizations invested in the smart home technology, or

ones that are currently considering entering the market. Providing

them with data that can guide the product development and design

decisions to improve their chances of adoption in the Canadian mar-

5


ket. Secondly, from the literature perspective, this research provides

information valuable to the research community where it poses new

theoretical models and propositions that can help future research.

After examination of the research material and the expected deliv-

erables, we anticipate providing value to the stakeholders in a number

of ways. The list of key adoption factors identified will allow organi-

zations and managers to develop their smart home technology using

specifications that lead to quicker consumers product adoption which

should enhance market share and profits. The components all form

relations with one another and play a role in the adoption model devel-

oped through this research, and we expect to find the developed model

to share a similar impact on other technologies affecting the market for

IoT technology.

1.5 METHODOLOGY

This research is conducted in multiple stages, utilizing the existing lit-

erature and bringing in value from data collected from a sample of

potential and current consumers of smart home technology through an

interview process. This process is conducted utilizing these five stages:

(1) Conducting a literature review followed by identification of the theo-

retical security factors that potentially influence adoption. (2) Selecting

a study sample and conducting semi-structured interviews. (3) Struc-

turing the collected research data and tabulating interview results. (4)

6


Analyzing of the data and identifying patterns. (5) Construction of

adoption model and proposition of factor relationships.

1.6 ORGANIZATION OF THE THESIS

This thesis is organized into six chapters, each structured into sections

and subsections. The first chapter introduces the research topic and

lays out the plan for the full article. Chapter 2, “Literature Review,”

examines the literature available on the subject and categorizes the

findings into streams then provides some key lessons. Chapter 3, “Re-

search Design and Methodology,” describes the methods used to con-

duct the research, develop the examination process, and the collection

of data. Chapter 4 documents the resulting data from the conducted

study and presents a summary of the results. Chapters 5 and 6 present

a discussion of the results and conclusions.

7


2 LITERATURE REVIEW

The literature available about the research topic can be categorized into

three self-contained and well-studied streams: (1) technology adoption

models, (2) boundaries of smart homes, and (3) cybersecurity and chal-

lenges in connected technology. Next, we briefly examine what the main

findings of the literature from each of the three streams and how it can

aid our research. (see Table 1)

Table 1: Literature Review Streams

Stream Key Highlights Key ReferencesTechnologyadoption models

Models of technology accep-tance have been modified tobetter explain adoption.Contradictions are noticedin the literature when themodels are applied to smarthomes.

Davis Jr(1986)Venkatesh et al. (2003)Venkatesh et al. (2012)Kranz & Picot (2012)Mayer et al. (2011)

Boundaries ofsmart homes

Examines the history andidentifies what makes asmart home. Shows a shiftfrom the technology basedidentification of smarthomes to interaction based.

Aldrich, (2003)Jiang et al. (2004)Alam et al. (2012)Camarinha-Matos & Afsar-manesh, (2014)

Cybersecurityand challengesin connectedtechnology

Identification of challengesfacing the future of smarthome technology, the litera-ture ranges from social bar-riers and speed of adapt-ability to cybersecurity andtechnological warfare.

Hong et al. (2009)Balta-Ozkan et al. (2013)Schrammel et al. (2011)Weber (2010)Komninos et al. (2014)Yang et al. (2015)

2.1 TECHNOLOGY ADOPTION MODELS

When we look to the past, organizations have always wanted to know

more about what factors and specifications provide their products with

8


a market leading position, and we find that reflected well in the litera-

ture. Technology adoption models emerged in the literature in the mid

1980s, thanks to the efforts of Davis Jr. (1986). Initially, researchers

provided a simple model, known as the technology acceptance model

(TAM), which provided a better understanding of user acceptance of

technology (see figure 1). Davis Jr.’s (1986) TAM model provided orga-

nizations with a theory for designing technology with higher potential

of success.

Figure 1: Technology Acceptance Model (Davis Jr., 1986)

Davis (1989) intended to develop a measuring scale to predict users

acceptance of the emerging and rapidly growing new technology of com-

puters. He initially hypothesized the existence of two fundamental de-

terminants of user acceptance as perceived usefulness and perceived

ease of use. The study found that both perceived usefulness and ease

of use were significantly correlated with self-reported indicants of sys-

tem use (Davis, 1989).

9


The model developed by Davis (1989) presents a strong relationship

between perceived usefulness and user acceptance. The effects of per-

ceived ease of use to acceptance were also observed but proved to be

less significant than that of usefulness. However for a product where

all else is equal, higher perceived ease of use will increase the user’s

attitude towards acceptance.

Perceived usefulness and ease of use formed the two key components

of adoption models and have remained in the literature stream as it

developed into larger models. Additionally, Davis’s (1989) research

provided some evidence that other external variables are favorable and

play a role in the user acceptance process. The external variables fac-

tor was further studied in future research as suggested by the researcher

The study concluded that users acceptance of computing technology

was determined by their perceived performance value. Davis (1989)

provides a future goal to better understand user acceptance by stating

“Given that this study indicates that people act according to their be-

liefs about performance, future research is needed to understand why

performance beliefs are often in disagreement with objective reality.”

Following Davis’s research, another very distinguished researcher in

the area of technology adoption is Viswanath Venkatesh who has pub-

lished multiple highly reputable research papers that have been refer-

enced by organizations and scholars. In earlier research, Venkatesh and

10


his colleagues produce a User Acceptance Model (see figure 2) that, to

them, outlines the basic underlying concept of all user acceptance mod-

els (Venkatesh et al., 2003). This Model does share some resemblance

to the technology acceptance model developed by Davis, as it shares

the users’ attitude towards technology, behavioral intent to use, and

actual system use under different phrasing. However, the model does

not take into account the effects of perceived usefulness, perceived ease

of use, or external variables at its current stage.

Figure 2: User Acceptance Model (Venkatesh et al., 2003)

Venkatesh and his colleagues kept developing their model through

the examination of the literature present at the time. A unified model

was developed through the review of eight models: (1) the theory of

reasoned action, (2) the technology acceptance model, (3) the motiva-

tional model, (4) the theory of planned behavior, (5) a model combining

the technology acceptance model and the theory of planned behavior,

(6) the model of PC utilization, (7) the innovation diffusion theory, (8)

and the social cognitive theory.

The resulting model from the unification in 2003 was called the Uni-

11


fied Theory of Acceptance and Use of Technology (UTAUT)(See figure

3), which refined the works of other researchers providing a model with

more variables and a higher interpretation of variance in user intention

(Venkatesh et al., 2003).

Figure 3: Unified Theory of Acceptance and Use of Technology(Venkatesh et al., 2003)

The UTAUT model has four determinants of user behavior, and four

key moderators to those determinants. The determinants are labeled

as: performance expectancy, effort expectancy, social influence, and fa-

cilitating conditions. Their key moderators are labeled as: gender, age,

experience, and voluntariness.

Performance expectancy is the perceived benefits in task performance

gained by using the technology. This determinant is similar to the per-

ceived usefulness component of the TAM model and is derived from that

12


model along with four other constructs of performance in other models.

Effort expectancy can be related to the perceived ease of use com-

ponent from TAM, where it pertains to the degree of ease associated

with the utilization of the technology.

The social influence determinant is determined by the effect other

people have on the user through their perception on the importance of

having and using the new system. This determinant is rooted in the

sociological study of social normativity.

The last determinant of the UTAUT model, facilitating conditions,

is defined by the existence of capability in terms of systems, organiza-

tions, and infrastructure to support the use of the new technology.

Four key moderators are identified in the UTAUT model, and each

of the determinants is related to one or more of these moderators. Age

and gender moderate performance expectancy. Effort expectancy has

its moderating factors as age, gender, and experience. Social influence

is the highest moderated with all four factors affecting the relationship

between social influence and behavioral intent. Facilitating conditions

are moderated by the age and experience of the users.

These adoption models have been studied and revised by many of the

leading experts. In 2012, Venkatesh et al. revised the UTAUT model

13


to include new variables. The resulting model is the Unified Theory of

Acceptance and Use of Technology 2 (UTAUT2), (see figure 4). This

revised and expanded model, through regular testing, could explain be-

havioral intention up to 74 percent (Venkatesh et al., 2012).

Figure 4: Unified Theory of Acceptance and Use of Technology 2(Venkatesh et al., 2012)

In the second iteration of their model, UTAUT2, Venkatesh and his

colleagues added three new variables that relate to the behavioral in-

tent of consumers: hedonic motivation, price value, and habit.

Hedonic motivation refers to the pleasure and fun that consumers

experience from using the new technology. Price value is the cost struc-

14


ture of acquiring the technology and maintaining operation and consid-

ers the different effects from consumers incurring the direct cost versus

being provided the technology through an organization that covers the

cost, such as receiving a company computer. The final determinant,

habit, is the tenancy of the user to perform behavior required for the

technology automatically.

The models mentioned through this section have been deployed in

real-life business applications to improve the performance of products

and increase the levels of their adoption to a particular demographic.

Literature on the application of the adoption models mentioned above

in real life citations is abundant, offering valuable insight into the af-

fects each of the determinants have on consumer behavior (Anderson &

Schwager, 2004; Kijsanayotin, Pannarunothai, & Speedie, 2009; Raman

& Don, 2013; Oechslein, Fleischmann, & Hess, 2014; Arenas-Gaitan,

Peral-Peral, & Ramon-Jeronimo, 2015).

Similarly to Venkatesh et al. (2012), other researchers have continued

to advance the model to provide a better explanation of the adoption

curves in different technology sectors. Studies have introduced to the

adoption model factors such as management effectiveness, program ef-

fectiveness, pervasiveness, health concerns, and socio-economic status

(Abdulwahab, & Dahalin, 2010; Segura, & Thiesse, 2015; Xiong, &

Mei, 2016). Upon examination of how these models behave in pre-

dicting smart home technology adoption, we find that the literature

15


provides contradicting results. The range of research into the future

of smart homes varies from suggesting that the industry needs to re-

think their product solution (Aldrich, 2003; Barlow & Venables, 2003)

to suggesting rapid growth in the next few years (Rose et al., 2015),

and others in between (Chan et al., 2008).

2.2 BOUNDARIES OF SMART HOMES

The second stream of literature about smart homes examines the core

concepts and identifies what makes up a smart home. Researchers that

worked in this stream focused on finding a definition for smart homes

as well as setting the boundaries of what technologies should classify

as smart home technology.

One of the earliest recorded mentions of the smart homes concept

can be found in the 1970 book publication of The Computerized Soci-

ety (Martin & Norman, 1973). The authors worked to disillusion the

public of the capabilities of computer technology of the day. As part of

their publication, they provided a vision of possible development in the

ten years to follow their book given what capabilities were available at

their time.

Among the list of automations envisioned by Martin & Norman

(1973) were online banking and e-transfers, computerized dispatch and

GPS navigation systems, computer-assisted education, electronic health-

16


care, and the smart home concept. They predicted that the smart

home of the future could control entertainment systems, allow for work

at home, and extend the educational system to connect to the homes.

The capabilities did not end there. Mention of automated appliances

and control through a mobile telephone give a shocking resemblance to

the modern smart homes technology.

Innovation in computing technology aided the evolution of the smart

home definition. Skrzypczak (1987) used a definition of smart homes

that again relied on the automation of technology through processor

units and envisioned the technology to be heavily present by 2010.

Skrzypczak also identified the smart homes through having a control

processor appliance incorporated into the home which would be capa-

ble of monitoring and controlling many functions of the household as

well as provide a connection to the outside world.

The creator of Xanadu (a vision of future smart homes), Roy Mason,

described the automated home of tomorrow with layers of capabilities

(Bruce, 1987). At the core of it, the “home brain” would be capable

of controlling the energy, lighting, and security systems in the house.

Above that core layer came an endless pool of possibilities in the form of

appliances that ranged from robots that could do house-cleaning jobs,

and kitchens that are nutritional diagnosticians, to three-dimensional

holographic art.

17


Moving forward with the technology, the industry focused on the

growth of cellular technology. As the new market picked up speed

during 1990, researchers began to investigate its possible future uses.

One article found smart home technology could grant the cellular tech-

nology a promising area for collaborative growth, mentioning how the

increased use of sensors in smart homes would extend the use of cellular

phones as remote control systems (Jarratt & Coates, 1990).

The literature available on smart homes grew more rapidly after the

1980’s as more articles gave definitions relating to smart homes. Key

features of the smart homes emerged commonly in definitions, such as

the purpose of smart homes in providing assistive technology, their po-

tential to monitor for needs, their automated responses to these needs,

and their connectivity to appliances around the homes (Allen, 1996;

Warren, Craft, & Bosma, 1999; Covington, Moyer,& Ahamad, 2000;

Aldrich, 2003). Emerging markets for smart home technology has be-

come more evident in the literature. Amongst these markets were secu-

rity, electronic health care, entertainment, and environmental control

(Warren et al., 1999; Aldrich, 2003; Chan et al., 2009). Within these

markets for the technology, a greater portion of articles focused primar-

ily on the electronic health segment (Bellazzi et al., 2001; Demiris &

Hensel, 2008; Chan et al., 2008).

We observe that although there are strong definitions for smart homes

provided in the literature, studies continue to provide their own under-

18


standing of what smart homes are. This has led to some conflicting

views and has kept the industry from setting an agreed standard for

the definition. In our study we firmly support the definition of smart

homes provided by Aldrich (2003) that states:

“A ‘smart home’ can be defined as a residence equipped with

computing and information technology which anticipates and

responds to the needs of the occupants, working to promote

their comfort, convenience, security, and entertainment through

the management of technology within the home and connec-

tions to the world beyond”.

The literature on smart home technology has been grouped into sec-

tors based on the functions they serve. These sectors are defined with

better clarity in more recently published articles. The distinct groups

identified by the literature are (1) home automation, (2) entertainment,

(3) security, (4) healthcare, (5) remote access control, and (6) energy

efficiency (Chan et al., 2008; Alam, Reaz, & Ali, 2012; O’Malley &

Munoz, 2014). As the boundaries of smart home technology becomes

clarified by researchers, the methods of identification used to separate

smart home technology has shifted from technology based to interac-

tion based.

More on the development of smart home definitions and what the fu-

19


ture of smart home technologies might hold are present in the literature

(Intille, 2002; Robles & Kim, 2010; Hamernik, Tanuska, & Mudroncik,

2012; Kadam, Mahamuni, & Parikh, 2015; Solaimani, Keijzer-Broers,

& Bouwman, 2015).

2.3 CYBERSECURITY AND CHALLENGES IN

CONNECTED TECHNOLOGY

The third stream in the literature revolved around the topic of chal-

lenges that have blocked smart home technology’s reach. Studies in-

dicated that, like many other early technologies, smart homes have

unresolved issues on a number of fronts. Research on this topic is of-

ten multi-disciplinary and heavily focused on one issue. To present the

issues clearly we present the literature separated by their selective pri-

mary challenge of smart homes technology.

2.3.1 Human interaction Challenges

In the move towards an integrated automated system for technolo-

gies within the homes, some researchers have investigated the human-

system interaction challenges arising from the design. Given that one

of the market sectors for this technology would involve elderly users for

their heath care needs, it comes as no surprise that researchers have

gathered information to challenges that they might face. In a set of

interviews with a group of older adults - over the age of 65 - one study

20


found that a pressing challenge for this demographic is the lack of user-

friendliness and the need for extensive training to operate the modern

technology (Demiris et al., 2004).

Addressing the interaction challenges present in this technology could

prove to have a larger impact on the market as it affects more that the

elderly demographic. Edwards & Grinter (2001) explain in a study

of the challenges of ubiquitous computing how the technology that has

been weaved into the fabric of the home will require its occupants to be-

come the systems’ administrator. The technology faces an operational

barrier as it moves from testing in a lab with state-of-the-art experts

to the home of an average consumer. Researchers have focused on the

technical limitations which have not been met, such as the collabo-

ration between different smart home systems and the human-system

interactions (Camarinha-Matos, & Afsarmanesh, 2014).

2.3.2 Social Barriers

It is part of human nature to accept and reject behavior based on its fit

with social norms; actions made by technology and machines are not

exempt from this judgment. Social barriers could impact the future of

smart home technology, suggesting that technology that is incapable

of fitting in with the pre-existing norms would be found unappealing

(Balta-Ozkan et al., 2013). Social barriers could include the level of

know-how required to operate the systems and the tolerance to errors

21


homeowners are willing to accept as Balta-Ozkan et al. (2013) indi-

cate in their research. The level of control required in smart homes to

technology that affects our daily lives challenges the boundaries of our

social settings. On this topic, Davidoff et al., (2006) share their ob-

servation that “Interestingly, expanding system capabilities can easily

overstep some invisible boundary, making families feel at the mercy of,

instead of in control of that technology.”

On the other hand, studies on the social development and impact

of smart home devices suggest possible advantages from this human

nature. As the technology is introduced into homes, the expected lev-

els of behavior and activities to be undertaken at home grows, effec-

tively broadening the scope of acceptability (Friedewald et al., 2005).

Meaning that as time goes by, people naturally grow to expect certain

behavior, making the availability of the technology part of the new

social norm. Observations made by a study of the impact of the pres-

ence of the automated robotic vacuums, Roombas, on the behavior of

householders provide evidence to support this social adaptation (Sung

et al., 2007). The research indicated the development of intimacy to

the robots, the attachment to the technology suggested social changes.

2.3.3 Cybersecurity issues

A major component of this stream of literature revolves around chal-

lenges caused by cybersecurity issues. The challenges of a smart home’s

22


cybersecurity are abundant and the literature is aware of the complex-

ity and inherent risk (Schrammel, Hochleitner, & Tscheligi, 2011; Yang

et al., 2015; Weber, 2010; Komninos, Philippou,& Pitsillides, 2014;

Hong, Suh, & Kim, 2009). Amongst many of the articles in this field,

it is noted that although they intend to present a clear picture of chal-

lenges in the future of this technology, the set of issues presented is

not exhaustive. With the increasing amount of ingenious ways people

are connecting technologies together, the front for cyber attacks grows

larger and with it so do the challenges relative to system security.

The challenge of cybersecurity has been separated into smaller more

observable sections in order to better study and explain its effects.

First, we must clarify how cyber attacks affect the technology and in-

formation within smart homes, then we move to the measures of a

consumer’s perceived cybersecurity of the technology. In studies, the

system can be compromised when one or more of the following six se-

curity objectives have failed: confidentiality, integrity, availability, au-

thenticity, authorization, and non-repudiation (Komninos et al., 2014).

The confidentiality of a system is generally related to the disclosure of

the data, and assurance that it is only accessed by authorized personnel.

Similarly, the integrity of a system reflects the degree to which it pro-

tects the data from unauthorized alterations and ensures its accuracy.

Access to the resources of the system at all times when the allowed in-

dividuals requires it is described by the term availability. Authenticity

23


refers to the capability of the system and its representatives in insuring

the identity of the people behind each interaction are known and who

they claim to be. The authorization process ensures the legitimacy and

roles assigned of access control to the system. Finally, the presence

of undeniable proof and evidence verifying every claim within the sys-

tem ensures its non-repudiation. In situations where any of these six

objectives are compromised on purpose or accidentally, the cybersecu-

rity protection of the technology and its users has failed. Such failures

could lead to the users being put at a financial loss and possibly affect

them in other ways that may increase their level of risk for fraudulent

behavior and identity theft.

The implications of harm by the security risks of smart home technol-

ogy extends beyond the cyber realm. The technology of smart home

systems is part of Cyber-Physical Systems (CPS), which presents an

additional set of challenges. Lee (2008) presents a definition of CPS

and examines the challenges that it faces in connected technology such

as smart homes. The provided definition for his research “CPS are inte-

grations of computation and physical processes. Embedded computers

and networks monitor and control the physical processes, usually with

feedback loops where physical processes affect computations and vice

versa” (lee, 2008). In a CPS risks impact the physical space and can

challenge the safety and reliability of such systems. Potential for harm

and risks by CPS are examined in articles such as (Banerjee et al., 2012;

Dutt, Jantsch, & Sarma, 2016; Lee 2008; Sha et al., 2008).

24


It is important to distinguish between actual and perceived levels

of cybersecurity. Perceived security, similar to the perceived risk, is

a direct factor that influences the consumers’ acceptance of a product;

whereas the actual level of security against cyber attacks does influence

the perception of a consumer about the product, nor their acceptance

of it. Examining consumer acceptance of electronic banking, Lee (2009)

documented evidence based on the TAM and the theory of planned be-

havior (TPB) model, which highlights the strong relation consumers’

perception of security and their attitude towards the product. Litera-

ture on the ways by which consumers perceive security in technology

products often refer to three major factors: privacy, safety, and trust

(Bellman, Lohse, & Johnson, 1999; Tan, & Teo, 2000; Miyazaki, & Fer-

nandez, 2001; Gefen, Karahanna,& Straub, 2003; Nissenbaum, 2004;

Lichtenstein, & Williamson, 2006). Each of the three major factors

have been covered by a number of researchers who have provided in-

sight into the definitions and the impact they have on smart home

technology.

The literature provides a definition for privacy that focuses on the

protection of the personal information for the occupants of the house-

hold. The protection of this information from disclosure to other unau-

thorized parties ensures the protection of privacy (Lichtenstein, & Williamson,

2006). Smart home technology relies in its operations on a continuous

connection to devices and services often provided over the Internet.

25


The personal information of users operating within their homes be-

comes open to the world and the privacy wall disappears (Chan et al.,

2008; Weber, 2010). Due to prolonged operation of occupants in close

quarters with the smart home technology, often consumers become un-

aware of the amounts of information collected by the technology, leaving

them vulnerable to exploitation.

Safety is defined as the protection of data as it is transfered across

the internet where it is kept at a low risk of unauthorized access or

manipulation (Lichtenstein, & Williamson, 2006). The terms selected

by some researchers for this factor could differ and is often given as

security; however, due to the generality of what that could encompass

especially as a component of cybersecurity, we favor using the term

safety. Government agencies have released publications researching the

safety factors of smart home technology as the impact of attacks lead

to the loss of control of IoT devices could affect the public’s well being.

Threats of IoT attacks have increased the risk of future warfare being

conducted through this platform (Yang et al., 2015).

The third major factor of cybersecurity is trust, which is defined by

how we expect the technology and/or service providers to act with our

best interest in mind (Lichtenstein, & Williamson, 2006). In the set-

tings such as those with smart home technology where there is a lack

of the typical human interaction, building trust can be very difficult

(Gefen et al., 2003) . From the introduction of online shopping till this

26


day, the topic of building trust over the internet has been the focus of

many researchers (Babar et al., 2010; Ziefle, Rocker, & Holzinger, 2011;

Mennicken, Vermeulen, & Huang, 2014).

To give a better visualization of how these three factors affect the

security objectives if the technology we provided a table below (see ta-

ble 2). The table indicates which of the six objectives would be subject

to attack for each factor. Note that depending on the nature of the

attack, it could affect any number of the major factors at once.

Table 2: Compromise of Cybersecurity Objectives by Component

Privacy Safety Trust

Confidentiality X X XIntegrity XAvailability XAuthenticity X XAuthorization X XNon-Repudiation X

Provided this encompassing understanding the question now is not

whether cybersecurity could be a barrier to the dissemination of smart

home technology, but of how big of a role does it truly play and how

can we better understand it and control it.

Other authors who examined the challenges in the future of smart

home technologies further have examined context awareness and au-

tomation security, efficiency and optimization challenges, and other

27


cybersecurity constructs (Robles et al., 2010; Jose & Malekian, 2015;

Chitnis, Deshpande, & Shaligram, 2016; Lobaccaro, Carlucci, & Lofstrom,

2016).

2.4 SUMMARY AND KEY FINDINGS

To conclude this chapter, we provide a brief summary of the informa-

tion presented and highlights of the key findings. We began by looking

at the evolution of the theories and models of technology adoption ob-

serving the difference from the simple TAM to the UTAUT2 model.

The addition of more factors helped improve the models’ accuracy and

usability. We presented some of the earliest definitions of smart home

technology and how such definitions evolved over time–making its way

from being technology based to a behavioral focused definition. The

literature kept pointing further into the future for when the technology

will be available in every home. In the third stream of the literature the

focus of future challenges gave us a look at how issues could stem from

human and machine interaction, through social barriers, and from cy-

bersecurity risks. We took a closer look into what makes cybersecurity

describing six objectives that should be maintained to keep the tech-

nology secure as well as three main factors that affect how consumers

perceive cybersecurity, namely, privacy, safety, and trust. Key findings

that presented high value information to our study are shown below.

Independent empirical investigations conducted with existing mod-

28


els on smart home adoption showed contradicting results on the rela-

tionships between factors and the adoption. Leaving us with widely

differing prospectives of of the future acceptance of the smart home

technology (Kranz & Picot, 2012; Mayer et al., 2011).

When it comes to homes and personal space, IoT devices have brought

along some new challenges. Given the close level of interaction and in-

tegration between the technology and the user of smart homes, new

considerations of privacy sensitivity are needed. Modifying the regula-

tion on informing the user or introducing restrictions from selling the

data (Schrammel et al., 2011).

The literature suggests three main components that make up cyber-

security and they are: trust, safety, and privacy. Trust is defined by the

ability of the user to trust in service providers to take the right action

towards their customers. Safety is about the transfer of data across

the internet without having any unauthorized access or manipulation

to that data during transfer. And finally, privacy is defined as the pro-

tection of the user’s personal information making sure it is not used by

or disclosed to others. The perception of these three parts combined

determines the level of cybersecurity provided in a product.

From the points made above we can expect for observation of con-

sumer behavior to indicate a relationship between cybersecurity and

behavioral intention, as represented by the figure shown below (See fig-

29


ure 5). The figure shows modifications to the technology acceptance

and adoption model, where the cybersecurity is a factor that is made-

up of three core components: trust, safety, and privacy.

Figure 5: Preliminary Theoretical Model: Smart Home TechnologyAcceptance

The importance of cybersecurity in smart home technology goes be-

yond the acceptance and adoption of the technology by consumers

largely because it affects the security of the general public. Studies

suggest that without robust cybersecurity measures, the next genera-

tion of war tactics will utilize the vulnerability of IoT devices to launch

attacks on a network-centric battlefield (Yang, 2015).

30


3 RESEARCHDESIGN AND METHOD-

OLOGY

This chapter presents the research design and details of the method

used to answer the research questions posed in Chapter 1. Specifically,

the research question sets out to find the role cybersecurity plays in

Smart Home technology adoption. This chapter is structured into five

sections: (i) overview (ii) methods and instruments, (iii) description

and details of the data collection, (iv) participants, and (v) importance

and limitations. The methods and instructions section describes the

overall research method and decisions taken in preparation of research

conduction. In the third section which focuses on the details of the

data collection, we emphasize important procedures that ensured the

validity and ethical compliance regarding data collection. The partici-

pants section describes all the actions taken in selecting and acquiring

volunteers to participate in the conduct of this research. Finally, the

last section examines the research’s overall value as well as when it

should not apply due to certain restrictions in the data collection and

analysis process.

3.1 OVERVIEW

We anticipate that findings would indicate when an organization sets

out to provide improved cybersecurity of their smart home technol-

31


ogy their product’s adoption rate should reflect an improved level of

acceptance. We investigate by collecting data through an interview

process with current and potential customers of smart home technol-

ogy. We provided a series of questions that aim to better understand

what factors the users consider before making a decision to purchase

the technology for themselves.

A summary of the steps of the research method is presented in the

table shown below (See Table 3). The table describes each activity and

its outcome. First, the research examines potential research methods.

Then, we describe the development and design of the interview script

and how it was conducted. Next, we highlight the ethical precautions

that were followed by the collection of interview data. Finally, the data

was transcribed in the fifth step.

This research leans towards an exploratory approach based on the

various challenges identified in the literature. To conduct the exploratory

research, we adopt the qualitative analysis method which avoids the

limitations of participants answers conforming to fit within required

parameters. By conducting semi-structured interviews, the researcher

could guide the conversation with the willing participants to the general

discuss of interest then leave room for an open interpretation by the

participant. The answers provided through this method can expand

our model of technology adoption with new factors that affect the con-

sumers behavior provided directly by the target market. Interviewees

32


Table 3: Steps of The Research Method

Step Activity description Outcome of the activity1 Research method

selectionThrough the understanding of supportive litera-ture and theories, we conclude the most suitableapproach to conduct the research collection. Re-sults indicate a qualitative approach with semi-structured interviews (pages 34-37).

2 Preparation ofinterview script

Construction of a semi-structured interview essen-tially relies on preparation of a script to lead theconversation towards obtaining responses that re-late to the research topic. Taking into account thethought process of the respondents during scriptdevelopment improves the validity of collected in-formation (page 37-39).

3 Ethical review Prior to the collection of data through participantinvolvement, a review of the potential ethical im-pact and risks posed on participants is required.The process greatly reduces the presence of biasand ensures consensual agreement of data collec-tion (page 37-39).

4 Conduct ofsemi-structuredinterviews

Identify the willing participants and arrange meet-ing to conduct individual interviews. Record theconsumers perception of smart home technologyand the influential factors involved in the accep-tance and adoption process (pages 39-40).

5 Transcription ofinterview recordings

Following the conduct of the semi-structured inter-view process, the audio recorded data from eachcompleted interview is transcribed. The writtentranscription is used in the analysis stage of theresearch.

are asked to provide what they believe the problems with the technol-

ogy are. We purposefully avoid indicating cybersecurity as a potential

factor to eliminate some of the biases in the study. more evidence sup-

porting the benefits of the qualitative research approach are presented

in the section below.

33


3.2 METHODS AND INSTRUMENTS

Research in the field of technology adoption has previously conducted

analysis in a similar fashion. Mallat’s (2007) qualitative study incor-

porated more situational factors in the adoption model. Additionally,

they identified additional barriers to acceptance. Other studies have

benefited from this analysis strategy for its capability to explain and

describe situations that are not familiar to the research field, such as the

prediction of smart home technology acceptance by the elderly (Renaud

& Van Biljon, 2008). The versatility of qualitative research in providing

a better understanding of emerging and growing markets makes it the

optimal choice for our research requirements.

To analyze the data from the qualitative research, we chose to use

a modified approach to Grounded Theory. This approach focuses on

themes emerging from the discussions and conversations. The advan-

tage to using this method is its capability to be primarily exploratory

in nature, enabling the research to discover additional constructs to the

adoption models (Glasser & Strauss, 1967; McCracken, 1988; Glaser,

2014).

There are five stages in our approach to analyze data from interview

data. Those five stages are described in the table below (see table 4)

and will be used in the discussion chapter to develop our theory.

34


Table 4: Steps of Conducting Modified Grounded Theory Analysis

Steps Activity description OutcomesStep 1 Two stage identification of key

observations from the transcribeddata

A series of quotes from each of theinterviews, and tabulated group-ing of participant answers (pages42-84).

Step 2 Observations are developed intodescriptive and interpretive cat-egories based on evidence pre-sented

The categorization of the datais process that affects the over-all organization and structure ofthe data. Selecting a balance be-tween labels that are close to theoriginal language of participantsand knowledge of previous theo-ries and findings (Each of the sub-headings under section 4.4).

Step 3 Identification of connections be-tween observations and develop-ment of patterns

We highlight and interpret rela-tionships in the interpretation offindings section (pages 91-97).

Step 4 Testing the fit of observationsagainst the developed patters andeliminating false patterns

Comparison to the literature ex-amining unexpected observationsand reflecting on propositions inthe implications of findings sec-tion (pages 91-97).

Step 5 Examining and grouping of pre-dominant themes contained in thedata to develop theory

Presentation of implication re-sults and development of the re-vised theoretical model (pages 95-97).

In this study, we selected target participants who are potential cus-

tomers of the smart home technology market. Providers and manufac-

turers of the smart home technology products and services were not

selected for the interview process to retain the focus on the acceptance

and adoption factors. The presence of cybersecurity in smart homes

technology relies on influence from both providers and consumers. How-

ever, in a new technology market for organizations to get ahead of

competitors and grasp the available opportunities, they must utilize an

exploratory based strategy of market-pull (Li et al., 2012). Research

indicates the acceptance levels of smart homes technology are higher in

35


user-centric approach and market pull strategy (Penaud, Mokhtari,&

Abdulrazak, 2004). In other words, in the study of consumer accep-

tance of emerging smart home technology the perception of the users

has a higher impact on the adoption of the product/service than the

perceptive of the providers.

To collect data for this research, we have selected a semi-structured

interview format which allows the researcher to adapt the interview

questions according to the progress of the discussion. The knowledge

of the participants towards the discussion and their prioritization of

some aspects provide insight into their behavioral motives. We draw

reference from Venkatesh & Brown (2001) for the development of our

questions used in the interview script, following a similar approach to

their research methods that have been supported by their peers. The

interview script was assessed for its presentation of required informa-

tion and minimization of the introduction of bias. Once the information

was found to be satisfactory, the script served as a guide to interviews.

To ensure that the goals of the interviews are retained through the

adaptation of the questions, we indicated the reason for selecting the

questions in the script. Hence, when the researcher has to adapt an

interview question to fit the situation, they can aim to find out in-

formation that can guide the data collection towards answering the

research question.

The interview script (see Appendix A) has been broken into two sec-

36


tions. The first is used to understand the factors in product selection

and adoption. And the second is used to identify the components of

cybersecurity. Each of the sections has a set of questions along with

goals for information identification. The goals are listed in the two

paragraphs below.

Based on information from the literature review, we have determined

that the first part of the interview should focus on the following five

issues. (1) Identifying the depth of the participant’s knowledge about

smart homes. (2) Setting a shared understanding of the definition of

smart home technology and what it means to the participant. (3)

Determining the interviewee’s willingness to own a smart home. (4)

Identifying the key factors the participant uses to make the purchasing

decision. (5) Finding the technology sector within smart homes that

the contributor associated with the most. This marks the end of the

first section of the interview script.

In the second section of the interview script, our aims are as follows.

(1) Identify the level of cybersecurity the participants are familiar with.

(2) Determine the relevance of the cybersecurity components to the par-

ticipant’s view of cybersecurity. (3) Find the level of importance each

component plays. This builds the relationships between the model’s

adoption factors.

37


3.3 DETAILS OF DATA COLLECTION

To ensure the utmost ethical conduct in the interview process, we re-

ferred to the Canadian Institute of Health Research et al. (2014 Decem-

ber) publication on proper conduct of research involving humans. The

publication provided guidelines for preparation and conduct of the in-

terviews. The procedures also ensured that selection, elimination, and

incentives to participants are within ethical standards. The tri-council

policy statement of ethical research conduction (Canadian Institutes of

Health Research et al., 2014) has been followed throughout the conduct

of this research to the fullest capability of all those involved. An appli-

cation was prepared by the researcher and supervisor of this research

which highlights the important information regarding the methods for

research conduct. Details of the information provided in the applica-

tion are given below.

The research protocol form included information on: the project

team, study overview, funding and approval, the participants them-

selves, recruitment methods of participants, informed consent, data col-

lection methods, data storage and analysis, declarations, and additional

comments. Additional information submitted along with the protocol

form included: consent form, interview script, recruitment poster, and

on-line recruitment material. The material was revised multiple times

by the researcher and supervising professor to meet the requirements

of the Canadian tri-council’s guide on the ethical conduct of research

38


involving humans.

The accepted ethical procedure for this research can be briefly de-

scribed as follows. There is no external source of funding to this re-

search by individuals or entities other than the researcher. Participants

interacted directly with the researcher through semi-structured inter-

view. The sample of participants did not include individuals with any

prior relationship to the researcher to eliminate any sense of obliga-

tion to participate or provide a specific type of answer. No financial or

commercial conflict of interest was present to affect participants, and

withdrawal from the research did not affect the compensation received

by the volunteers. Contacting interviewees was accomplished through

both posters on the campus grounds and posts on social media. The

research conducted involved 25 participants who had met the qualifi-

cation criteria and were willing to sign consent forms to carry out the

interviews properly. Participants in the study would not be subject

to any additional level of risk than experienced in daily life. Writ-

ten consent forms were signed by both the participant and researcher

prior to any data collection, with clarification on the nature of the re-

search, withdrawal procedure, and insuring that any questions by the

participants were answered clearly. An audio recording of the inter-

view process was acquired with consent of the participants for future

transcription of the data. Collected data is coded and anonymized,

removing any identifying information. Throughout the research period

all data is kept on a secure device stored in an encrypted format and

39


password protected. All recordings of participant information will be

destroyed after one year of research completion to ensure their privacy

protection.

3.4 PARTICIPANTS

Following the completion of the ethical review process, collection of

willing volunteers begun. This stage involved posting fliers and infor-

mation on social media sites that informed any interested individuals of

the ongoing study. Information on the title, purpose, and requirements

for the study was provided through the postings with instructions on

the method of contacting the researcher if an individual was interested

in participation. Participating in the study was voluntary for those

who fit the criteria. As an incentive to participate in the study, the

researcher provided a gift card to Starbucks R©.

For the purposes of this study, we chose our the sample of volunteer

participants based on four qualification criteria.Volunteers had to be

over the age of 18 to be of legal age to make a purchasing decision for

a home and be considered as potential customers. The interview script

was prepared in English, therefore, fluency in the English language

was selected as a required qualifying criterion. The qualifications also

required candidates to have spent at least two years living in Canada to

ensure that the participants had experienced the same standard of daily

living and amenities reducing any errors caused by cultural differences.

40


Finally, to qualify for the study, participants must indicate an intent to

purchase a house in the near future or within the past one year. This

last criterion is essential to ensuring that the participants are potential

customers of the smart home technology.

3.5 IMPORTANCE AND LIMITATION

The study was conducted in a manner to ensure the results could be

widely applicable to the smart home technologies. However, the study

sample sets a limitation to the global representation. In the interest

of feasibility, we chose to conduct 25 interviews with participants who

have spent at least two years in Canada, the small sample size in the

geographic restriction is not representative of consumers external to

Canada.

41


4 RESULTS

Chapter 4 presents the results of the study, and it is organized into

four sections. The first section gives an overview of how the research

data was acquired and who the participants were. The following two

sections correspond to the structure of the interview script, beginning

with the overview of consumers’ awareness of smart homes followed by

their predisposition to cybersecurity. The fourth section of this chapter

goes into greater detail of the participants’ responses from each of the

eight aims identified on the interview script.

4.1 OVERVIEW

To reiterate, the research question covered by this study is: what role

does Cybersecurity play in Smart Home technology adoption by con-

sumers in the household market. Findings from the literature review

chapter (earlier) provided evidence of a literature gap. A portion of the

literature focused on identifying adoption factors for the smart home

technology (Kranz & Picot, 2012; Mayer et al., 2011). A variety of

factors which play a part in the consumer acceptance of smart homes

are proposed by these studies. However, the studies do not include

cybersecurity as a factor in the technology adoption process. On the

other hand, we observe a separate portion of literature that examined

the challenges in the future of smart homes (Komninos et al., 2014;

Yang et al., 2015). Identified in this second group of research are a set

42


of cybersecurity challenges that can affect the experience of living in a

smart home. Given the indications in the literature to the importance

of both portions, we aim to study a crossover of both streams.

The literature provided theories which guided the creation of a pre-

liminary theoretical model of smart home technology adoption. The

model does not eliminate from the existing theories in the literature

but builds on the UTAUT2 model discussed in chapter two. Based

on arguments presented earlier, we propose that a link exists between

cybersecurity and a consumer’s behavioral intention. The theories also

indicate components that form and affect the intensity of cybersecurity

as a factor. A diagram representation of this theoretical model is pro-

vided earlier in chapter 2 (see figure 4).

We received a total of 34 volunteers interested in participating in the

study. From these, seven volunteers were not involved in the interview

process because they either failed to qualify or were unable to sched-

ule a meeting time to go through the 45-minute interview. From the

remaining 27 participants, two chose to withdraw their data from the

study leaving 25 remaining. The findings from the study sample are

summarized in the following sections. A demographic breakdown of the

25 remaining participants is shown in the table below (see table 5).

43


Table 5: Participant Demographics

Interview

Number

Gender Age

Group

House

Ownership

Education Employment

1 Male 18 - 24 Currently

Searching

High school

graduate

Part time job


Searching

Some College /

University

Student /

Part time Job


Searching

University

Graduate

Full time Job

4 Male 25 - 29 Owns University

Graduate

Full time Job

5 Female 18 - 24 Currently

Searching

Some College /

University

Student /

Part time Job


Searching

University

Graduate

Full time Job

7 Female 25 - 29 Owns College Graduate Full time Job

8 Female 35 - 39 Owns Some Postgraduate

Work

Two Full

time jobs

9 Male 18 - 24 Owns Some College /

University

Full time Job


Searching

Post Graduate

Degree

Full time Job

11 Female 30 - 34 Owns Post Graduate

Degree

Two Full

time Job


Searching

Some College /

University

Student /

Part time Job


Searching

Some College /

University

Student /

Full time Job


Searching

Some College /

University

Student

44


Interview

Number

Gender Age

Group

House

Ownership

Education Employment


Searching

High school

graduate

Full time Job


Searching

University

Graduate

Full time Job


Searching

High school

graduate

Full time Job

18 Male 40 - 44 Owns University

Graduate

Full time Job


Searching

Some College /

University

Student /

Part time Job


Searching

Some College /

University

Student /

Full time Job


Searching

College Graduate Full time Job

22 Male 25 - 29 Owns Some College /

University

Full time Job


Searching

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4.2 CONSUMER AWARENESS OF SMARTHOMES

During the interview, volunteers were asked to describe their level of

technical knowledge. Information collected through the interview pro-

cess indicates a normal distribution of the participants’ technical knowl-

edge (see Figure 6). When participants provided non-descriptive or

subjective answers, they were asked to provide an indication of their

regular activities with technology. This information was then mapped

onto a five step competency scale; from “Fundamental Awareness” to

“Expert” (National Institutes of Health, 2014).

Figure 6: Distribution of technical knowledge

2Fundamental Awareness7Novice7Internmediate

6Advanced3Expert

0 1 2 3 4 5 6 7 8 9 10Number of Participants

Participants answered if they have any prior knowledge about smart

homes if they gave a positive answer the researcher would follow-up

with a question asking them to provide a definition of smart homes.

From the sample, 20 participants had prior knowledge of smart homes,

and they provided their definition of smart homes. Of these 20 par-

ticipants, three provided definitions that were inadequate to properly

identify the technology, seven provided definitions that shared similar-

46


ities with the literature, and then gave full definitions that included

multiple key components of smart homes.

From the sample drawn two participants currently owned smart home

technology, the 23 other volunteers indicated if they were inclined to

install smart home technology in the future or if they were against

it. Seven participants were opposed to installing smart home until

their concerns regarding cybersecurity were met, and 16 participants

indicated their interest in owning a smart home provided the right

circumstances.

4.3 CYBERSECURITY PREDISPOSITION

In the second part of the interviews, we study the intensity of cyberse-

curity as a factor and what components contribute to cybersecurity as

an influence on consumer acceptance.

An examination of the interview scripts indicated that 16 of the 25

participants mentioned some component of cybersecurity being a factor

of concern to them when considering a smart home technology.

Out of the interviewed sample, the study found that six volunteers

had some prior knowledge or training in cybersecurity. Each of the

six participants had precaution measures in place to increase security.

From the remaining 19 interviewees, 13 members had taken some pre-

47


cautions without any training or extensive knowledge of cybersecurity.

Participants were asked about their perception of risk to their infor-

mation or belongings being affected by cybercrime. The result was an

almost even split with 12 participants indicating a high level of per-

ceived risk and 13 participants showed low perception of risk.

4.4 INDEPTH EXAMINATION OF RESULTS

The interviews with the participants collected information to aid in

the understanding of smart home technology adoption. Questions pre-

sented by the researcher were grouped into sets according to their aim.

The following subsections provide an in depth presentation of the re-

sults for each of the eight sets.

4.4.1 DEPTH OF TECHNICAL KNOWLEDGE

As mentioned earlier the five point mapping of the participant’s level

of technical knowledge was based on the National Institutes of Health’s

(2014) competencies proficiency scale (see table 6).

Table 6: Competencies Proficiency Scale

Score Proficiency Level Description

N/A Not Applicable You are not required to apply or demonstrate

this competency. This competency is not appli-

cable to your position.

48



1 Fundamental Awareness

(basic knowledge)

You have a common knowledge or an under-

standing of basic techniques and concepts.

2 Novice

(limited experience)

You have the level of experience gained in a

classroom and/or experimental scenarios or as

a trainee on-the-job. You are expected to need

help when performing this skill.

You understand and can discuss terminology,

concepts, principles, and issues related to this

competency.

You utilize the full range of reference and re-

source materials in this competency.

3 Intermediate

(practical application)

You are able to successfully complete tasks in

this competency as requested. Help from an

expert may be required from time to time, but

you can usually perform the skill independently.

You have applied this competency to situations

occasionally while needing minimal guidance

to perform successfully.

You understand and can discuss the application

and implications of changes to processes, poli-

cies, and procedures in this area.

49



4 Advanced

(applied theory)

You can perform the actions associated with

this skill without assistance. You are certainly

recognized within your immediate organization

as “a person to ask” when difficult questions

arise regarding this skill.

You have consistently provided practi-

cal/relevant ideas and perspectives on process

or practice improvements which may easily be

implemented.

You are capable of coaching others in the

application of this competency by translating

complex nuances relating to this competency

into easy to understand terms.

You participate in senior level discussions

regarding this competency.

You assist in the development of reference and

resource materials in this competency.

50



5 Expert

(recognized authority)

You are known as an expert in this area. You

can provide guidance, troubleshoot and answer

questions related to this area of expertise and

the field where the skill is used.

You have demonstrated consistent excellence

in applying this competency across multiple

projects and/or organizations.

You are considered the “go to” person in

this area inside or outside your immediate

organization.

You create new applications for and/or lead

the development of reference and resource

materials for this competency.

You are able to diagram or explain the relevant

process elements and issues in relation to orga-

nizational issues and trends in sufficient detail

during discussions and presentations, to foster

a greater understanding among internal and ex-

ternal colleagues and constituents.

Adapted from the Competencies Proficiency Scale provided by the National Institutes of Health (2014).

51


The majority of participants indicated their technical knowledge pro-

ficiency level was equivalent to novice or intermediate scale, with a

smaller portion represented by the advanced skill rating, and even fewer

qualifying as experts and fundamental awareness respectively.

A participant with only a fundamental awareness proficiency level

described their technical knowledge as follows;

“As far as electronics and stuff I have ideas on how these things work,

but I wouldn’t be able to operate [smart homes technology] by myself. I

have never really used that technology before” (participant number 10).

Other participants provided responses that indicated their belonging

to the novice or intermediate levels of proficiency, such as the ones

shown below.

“I see my level of technical knowledge to be very similar to people

in my age group [early twenties], I grew up with technology being ev-

erywhere around me. An even though I didn’t study computer science,

I still picked up a lot of things that my parents didn’t” (participant

number 7).

“I am not terribly advanced when it comes to technology, although

I do manage a [cellular service] store so when it comes to cellphones, I

am fairly savvy” (participant number 8).

Advanced technical skill levels were also demonstrated be a portion

of the participants. Some responses are provided next.

52


“I am very comfortable using technology, I program sometimes and

have a good understanding of how computers and electronics work [...]

I have used some smart home technology before, I see its benefits in

making things easier” (participant number 9).

One of the interviewees who categorized as an expert in technology

gave the following answer.

“Well, I am a computer programmer, with a lot of technical knowl-

edge. I have my own smart home devices, and I have done my own

research on [the cybersecurity of IoT] topic as well” (participant num-

ber 11).

4.4.2 DEFINITION OF SMART HOME TECHNOLOGY

The given definition by the literature on the meaning of smart homes

does not always reflect the common understanding shared by the gen-

eral public. The interviews provided insight into how consumers define

the technology.

The extent of understanding exhibited by the participants generally

followed one of two types. On one hand, people gave examples that

included different types of IoT devices connected together providing

value for the home owners, and the other group gave a vague discretion

of one product that could be associated with smart homes.

“I imagine it would be a house the interacts with your phone, and

technology so security cameras, [thermostats], lighting, maybe locking

53


doors, starting the dishwashers, and operating Roombas or something.

All that could be controlled together and work better together” (par-

ticipant number 20).

“It would be like home monitoring, things like that. That’s pretty

much all I know. Every time it gets advertised it’s about keeping your

home safe and monitoring it” (participant number 8).

The two examples provided above belong to two participants who

have both indicated having very little prior knowledge of smart home

technology. Both participants demonstrated similar technical profi-

ciency levels ranking them both at intermediate. The lack of a common

definition of smart home technology is also reflected in the literature,

and with service and product providers aiming to capture a larger share

of the market, the dilution of the border that defines smart home tech-

nology keeps increasing. Theory suggests that a common understanding

can be reached if we move away from the technical based definitions

and into a behavioral focus. We explored the reactions of participants

to a behaviorally based definition in the interview process and observed

a bridging in the divide.

The researcher presented Aldrich’s (2003) definition of smart homes

to the participants and asked for their feedback after they had provided

their own definition. The two participants provided above responded

as follows respectively.

“That sounds reasonable and good. It sounds exactly like how I

54


would have hoped to answer” (participant number 20).

“For me, it reminds me of a few other things that I have heard about

smart homes, and it’s just the whole idea of it being intuitive and learn-

ing things making it easier for you. Makes life simple and would also

make life more efficient” (participant number 8).

Participants of the study unanimously agreed with the definition

provided by Aldrich (2003), and highlighted any concepts that their

definition missed as being valuable to the technology.

4.4.3 WILLINGNESS TO OWN SMART HOME TECH-

NOLOGY

We examine the current willingness of the users to purchase the tech-

nology in order to understand what factors are at play that have helped

them make their decision. From the sample of participants, two already

owned some smart home technology. The technology components of

smart homes that those participants had included home automation

devices, entertainment systems, home security systems, and energy ef-

ficiency. From the complete sample eighteen participants were at the

time being in favor of purchasing smart home technology and seven

participants were against. To compare the relationship between the

level of technical knowledge and the consumers willingness to purchase,

we show below answers from four participants, two that have demon-

strated high technical skill (rating at four or five) one in favor and the

other opposed to installing, and similarly from two participants with

55


low technical knowledge (ratings of one or two).

From the strong technical proficiency group, a participant indicated

their willingness to own the technology (as shown below) when asked

by the researcher of how they would feel about owning smart home

technology.

“I am intrigued by the technology and interested in eventually hav-

ing something like it installed in my home. I would say I have had a

positive experience so far” (participant number 14).

But when the conversation changed to the topic of convenience and

risk the participant had more concerns about some of the risks associ-

ated with the technology.

“I see lots of small superficial benefits to a lot of these devices, but

there are also a few major things like security where I think smart

homes can come into their own, if proper security precautions are in

place there are only so many ways you can get around it. I think com-

ing in and out of the house easily is something a lot of people would be

interested in installing, and maybe garage doors that open when you

drive up to them, but those come with a lot of security risks which

make me hesitant” (participant number 14).

On the other hand, another participant who ranked as an expert in

technical knowledge was opposed to the idea of installing smart home

technology. Even though they were of highly advanced technical knowl-

56


edge, their inclination to learn more about the technology was an im-

portant factor to consider before trusting it.

“I don’t think it would be a good idea. I wouldn’t be comfortable

installing something I don’t know too much about. But if I could trust

and be convinced the my privacy is a high concern to the provider then

I would consider it” (participant number 19).

Looking at the low end of the technical skill spectrum we observe

a clear shift in the concerns that make participants opposed to the

technology. A Novice in technology focused on their lack of need for

the technology as the reason they wouldn’t spend the money on owning

the devices over their cybersecurity risks.

“No I wouldn’t, but it’s definitely something I would invest in if I re-

ally had the need for it. I mean the products I see are like thermostats,

the cameras, and the doorbells, things like that so those are all things

that right now to me I don’t have a use for I guess but not that I don’t

see the use for them ... I wouldn’t say I’m scared of the privacy risks or

anything like that, it’s no different that surfing the web realistically”

(participant number 4).

Similarly we see different behavior in participants who have ranked at

a two or one on the technical proficiency scale with a positive attitude

to installing the technology where there is no display for concern for

any risks associated with the technology.

“Coming from someone who is [unhappy with their thermostat] and

57


has never had the luxury of a security system in their places of residence,

I would love a Smart Home. The idea of having technology at my

fingertips to adjust whatever I desire in my home is really appealing

to me ... So much stuff that would save a person time and energy

that they could put towards things like a career, hobbies, enrichment,

exercise, etc. and so much less to worry about” (participant number

7).

4.4.4 WHAT ARE THE KEY FACTORS AND CONCERNS

As we observed in the consumer’s willingness to own section there as

factors that inevitably play a role in the purchasing decision. We asked

participants to indicate which of these factors they could identify fol-

lowing the question of their current intent to purchase. Participants

indicated what motivated them as well as what concerned them about

this technology. A summary of the key factors identified be participants

is given in the table below (see table 7).

58


Table 7: Key factors

Num Factors

Identified

Number of

Participants

Consumer Provided

Explanation

#1 Performance

and convenience

Benefits

15 “I would look into what kind of things I would

like to have made easier and see if I could save

on a few things or make them more convenient”


“I would have a house that would know some

things, so it could start making coffee as you get

up, or preferably before you get up so that it is

ready to drink as soon as you are awake. Ev-

erything would be pre-laid out you might have to

manually adjust a few things but the house will

start working on chores for you from morning till

night” (participant number 13).

#2 Security Risks 9 “Having your home run by technology it’s just

one of those things with fear from hackers. So it’s

one thing to have your laptop or phone hacked,

and with more Internet banking now on smart

devices, just to think that your entire house is on

a connected network like that. I guess there would

be a high trade off from risk for the convenience”


“I have limited my use of smart home devices to

things that don’t harm me if they get hacked.

When it comes to the [wireless door locks] I will

need to consider the level of security and authen-

tication on the device” (participant number 11).

59


Num Factors

Identified

Number of

Participants

Consumer Provided

Explanation

#3 Installation and

Operation Costs

9 “My biggest factor for not installing is cost.

My living situation right now as a student, I

don’t see it worthwhile to go through all that

renovation expense. Maybe sometime down the

road” (participant number 2).

“The thing is, I would have to spend more time

on researching it to decide if I am able to afford it

and if the level of smart home technology I could

get would make me feel safe. With the cheaper

options, you just can’t be sure if they will work

properly” (participant number 9).

#4 Restricted

Living Space

5 Some participants could not install smart home

technology because of restrictions in their living

area, either due to the small size or caused by

shared ownership which could be problematic if

the technology was not agreed on by all members.

“My apartment is very small right now, maybe if

I move to a bigger house down the road I would

be more interested in automating my house”


“I would change some of the things and maybe get

my house to be more energy efficient, as long as

it isn’t against my condo agreement” (participant

number 12).

60


Num Factors

Identified

Number of

Participants

Consumer Provided

Explanation

#5 Time and

Energy Savings

4 “Having some of these services like self-regulating

temperature or fridges that keep track of the

foods expiration dates there are many things

that could save a person energy and time. You

could optimize your monthly electricity usage and

get a lower bill with all the information avail-

able at the tap of a screen” (participant number 7).

“It could make me more productive, it can take

care of simple tasks for me here and there. What I

am thinking right now is mostly heating and light-

ing control. If a system is specifically monitor-

ing that all the time, it can become more efficient

in operation than any person could do manually”


#6 Lack of Trust 3 “Based on what I see from TV I wouldn’t trust

any form of automated intelligence to control

what I do in my home, I would need to have some

form on a kill switch” (participant number 7).

“I think I would be concerned with how the

provider values my information, and I wouldn’t be

convinced that they deserve my trust until I try

it” (participant number 19).

61


Num Factors

Identified

Number of

Participants

Consumer Provided

Explanation

#7 Lack of Social

Norm

3 “I would have to see it being used in practice

before I know if I am willing to make the trade

off” (participant number 3).

“A factor that would help me decide is if other

people say that the product is good and they have

used it” (participant number 14).

#8 Learning curve

and ease of use

3 “It’s important for me to have a good under-

standing of how it all works and be comfortable

controlling the technology when I install it in my

home. So I would need to do more research about

it first” (participant number 9).

“How well the interface is designed. I know there is

a whole bunch of different smart home technology

with different designs, and I think some of them are

really annoying. So I want something that is easy

to understand, and being able to have all of the

different technologies share the interface and have

a more consistent look and feel to them instead

of it being all over the place” (participant number

12).

62


Num Factors

Identified

Number of

Participants

Consumer Provided

Explanation

#9 Value of the

Technology

2 Two participants indicated the value gained from

the technology is a factor to them, however one

saw it as positive influence and the other saw the

lack of current value as a negative. Their opinions

are shared below respectively.

“For the simple fact that everybody has such a

busy lifestyle now, people don’t have the luxury

of a stay at home parent, everyone is working, I

would be more inclined to using the technology.

So anything the would make my life easier and

would allow me to spend more time with my

family and take a load of my shoulders sounds

fantastic” (participant number 8).

“With the type of place I live in there isn’t much

I can use the technology for. and living in a rural

area I don’t see much of a point just because if

something goes wrong it’s a lot more of a headache

to try to get it fixed” (participant number 5).

#10 Reliance and

Reliability

2 “I feel that if I do get smart home technology that

within a few months I would become very lazy. It

might become a problem if I just expect to have it

at all time. What would happen if it breaks down

at some point. If the system gets faulty and it

messes up the comfort of your home there needs

to be a manual override” (participant number 20).

63


Num Factors

Identified

Number of

Participants

Consumer Provided

Explanation

#11 Accessibility 1 “A valuable feature that my smart home has is

the ability to make changes while I am away. I

can change the temperature of the house, monitor

activity in the house, and turn some things on or

off. And I can access that from all of my devices”


#12 Lack of Privacy 1 “I wouldn’t be comfortable installing something I

don’t know too much about. But if I could trust

and be convinced the my privacy is a high concern

to the provider then I would consider it” (partici-

pant number 19).

#13 Closed Software 1 “I am a supporter of free and open software. In a

closed software product manufacturers could place

back-doors to their products and other insecuri-

ties. I don’t think that there are any open soft-

ware smart home products out there” (participant

number 3).

#14 Retrofit 1 “A concern for me would be that it is hard to

retrofit smart home technology into an already

built house. It’s not impossible, of course, but it

would be expensive. I would much rather have a

house that has been designed to include the tech-

nology in the first place” (participant number 13).

Aggregated results from the interview data collected

4.4.5 TECHNOLOGY SECTOR

Earlier in the study we identified six market sectors for the smart home

technology: (1) home automation, (2) entertainment, (3) security, (4)

healthcare, (5) remote access control, and (6) energy efficiency. We

64


asked participants in the study how they would use smart home tech-

nology in their daily life to identify which of these sectors they associ-

ated with. The data is represented in the figure below (see figure 7).

Figure 7: Technology Sector Distribution

13Home Automation8Energy Efficiency

5Remote Access Control4Entertainment

3Security

1Healthcare

0 3 6 9 12 15Number of Participants associated

The home automation technology sector was an area of interest for

the largest portion of participants, as 13 participants in total men-

tioned that sector of technology from the sample. An example from

the interviews is given below.

“I see the technology helping with my daily routine, for tasks that are

easy to [perform] with smart home technology. Maybe some lighting

control, at certain times, preparing coffee. I’m more into those tech-

nologies than major home security devices” (participant number 14).

The second largest sector identified by the contributers was the en-

ergy and efficiency sector. One of the eight responses that contained

that sector is listed next.

“I think it would make my life easier in several small ways but I think

65


things like having easier control over my living situation are going to

be much more important. Being able to instantly monitor how much

electricity my house is using, and what is using the most energy” (par-

ticipant number 2).

Five of the participants indicated an association with the remote

access and control functionality of smart home technology. A portion

from the interview is provided below.

“It would make some things easier. To some level it would increase

laziness by letting me adjust electronics around my house without mov-

ing, like my lighting and heating, but that is also important when I am

away from the house” (participant number 9).

In some situations interviewees indicated how they could use the

systems as a source of entertainment, those were present in four of the

interviews. An example is given below.

“I would probably become a lot more lazy to be honest with you if

my day could be regulated like that. I would just probably feel happier

and more content with my way of living. I would probably connect it

to my home entertainment center and get to play my music anywhere

in the house. It could also take care of a certain level of my daily tasks”


Three participants provided answers that indicated their interest in

utilizing the security measured of the technology. An example is listed

66


next.

“I would have more security, all my devices would be connected, and

it all works together. The doors would be able to know when someone

is there and who should be allowed in. I could monitor my kids when

I am at work. I think it would make my mind at ease” (participant

number 13).

The least represented market sector for the smart home technology

amongst this data sample was the healthcare sector. Only one partici-

pant associated the technology with being used to monitor the health

of occupants and improve their way of life.

“I see value from having this technology that would outweigh the

risks we discussed. Especially in a situation where there are special

needs at the home. For [some people] with limited mobility the devices

that can be installed would allow [them] to live freely” (participant

number 7).

4.4.6 FAMILIARITY TO CYBERSECURITY

Identification of the participant’s awareness and standard precautions

for their cybersecurity provides a bench mark to how they behave when

operation technology and is important to consider when they indicate

if such a factor could be a barrier to their adoption.

From the interviews, six participants indicated that they had received

some form of training or had been self taught in skills that relate to

cybersecurity. The remaining 19 participants where not familiar with

67


any form of training.

A participant indicated their knowledge in cybersicurity by indicat-

ing why they were required to undergo some training on the subject.

“I am from a military family so we have all received some training on

how to keep our technology and information safe” (participant number

8).

Another participant who had not gone through certified training pro-

grams indicated that their knowledge on the subject gained be conduct-

ing research on their own.

“I make sure that all my critical and personal information is either

stored on non-digital form, or kept in an encrypted format on an iso-

lated device. Like on a flash drive or external hard drive that are not

connected to any device unless something needs to be accessed” (par-

ticipant number 9).

Other participants with a low level of knowledge on the matter indi-

cated that their was no motivational factor for them to learn more in

the skill.

“I don’t know a lot about it. I have password on my devices, but I

wouldn’t do anything too complicated” (participant number 5).

Besides the level of training in cybersecurity we examined the partic-

ipants’ practices and precautions that they would regular use operation

68


of technological devices. 18 of the participants had anti-virus or anti-

malware software set up on some of their devices to provide some form

of low level protection to their technology and information.

One of the participants with no cybersecurity training or knowledge

had this to say about their precaution measure when operating tech-

nology.

“I use things such as anti-virus and anti-malware, I stick to the sites

I know and trust on the Internet. Basic things that everyone says you

need to have” (participant number 10).

Every participant that had indicated having training or knowledge

in cybersecurity also ran some form of anti-virus protection. Partici-

pants were more inclined to not have anti-virus software if they had no

knowledge in cybersecurity. From the 19 participants with the low level

of awareness in cybersecurity, seven had not operated their technology

with the protection of anti-virus software.

A sample of the participants’ responses to the inquiry on their stan-

dard measures of precaution are given below. The first is of a partici-

pant who was skeptical about the value of installing anti-virus software

instead relying on avoiding suspicious links on the Internet.

“I don’t click on ads, I have my firewall on, and I use long passwords.

That is the extent of my precautions” (participant number 7).

69


From another participant we get a responses that indicates they feel

completely protected without needing anti-virus technology guided by

some information that they had heard about the security of Apple’s

products online.

“I wouldn’t open emails that I am not sure where they are from.

But that is about it. I have a Macbook which is secure and doesn’t

need any anti-virus. Also, I don’t really download [movies or videos] I

usually stream it to be safe” (participant number 16).

Making sure that the participants’ level of cybersecurity is repre-

sented accurately we continued to probe by asking if they felt that

their information or technology would be vulnerable or targeted by cy-

ber criminals as it is at the time. This set of questions then resulted

in a larger divide in the sample where 13 out of the 25 participants felt

their electronics and information was secure in its current state while

the remaining 12 were opposed to them.

From the seven participants who had not chosen to use anti-virus pro-

tection on their devices and had a low awareness in cybersecurity only

one indicated they could be vulnerable in their current state (shown

below).

“My answer hinges entirely upon my insignificance in the great as-

pect of things [...] That said if I did have a cause for concern that I

was to be targeted I don’t believe that it would be very difficult for

someone with the know-how to get into my stuff, unfortunately” (par-

70


ticipant number 7).

Moving to the portion of the interviewees that have low cybersecu-

rity knowledge but did indicate the use of protection software on their

devices. Six of the 12 answered that they where vulnerable while the

other half answered that they were not.

Some of the participants in this group had an attitude that their

information was not of high value to anyone making their risk levels

low enough to not require any additional precautions to the measures

they had in place. An example is shown below.

“I feel pretty secure. I am not very important, and even if I was

targeted I don’t feel that it would reveal anything particularly compro-

mising” (participant number 3).

The other part of this participant group resorted to keeping infor-

mation which they felt was valuable off of their electronic devices or in

a more secure format which they felt comfortable with. “My attitude

towards the information that i put online and my own personal infor-

mation. I treat it all as though it is not mine. I have an understanding

that I cannot have total privacy over anything I upload. I do feel like

it is targeted, not particularly because of me of course but I feel like it

isn’t private” (participant number 2).

The remaining participants (six people) were participants which had

71


a higher level of knowledge in cybersecurity through training or be-

ing self educated on the matter. though all six indicate that the use

anti-virus protection on their devices, some of them responded to the

vulnerability questions with some lack of risk expectancy.

Two participants had indicated that they haven’t observed any in-

crease in cyber attacks over the past few years. They generally at-

tributed the heightened scene of concern for cybersecurity to the growth

in media and its interest in the topic. A participant had the following

to say.

“I really can’t say that there are more [cyber] attacks going on now

that before. So in a scene I don’t feel that I am facing any higher risks

now” (participant number 8).

Although the two participants had some disagreement with the state-

ment presented by the interviewer around their perspective on personal

vulnerability through reflecting on the increased number of reported cy-

ber attacks in the media, they still felt that some risk was present.

The last four participants have given cybersecurity the highest level

of familiarity out of all the others. they are knowledgeable and cyber-

security standards, their devices are protected by anti-virus and other

precautionary measures of securing information, and they are concerned

for the vulnerability of information and electronic devices they use reg-

ularly.

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One interviewee gave us the detailed view of their perspective on

vulnerability of information in the digital age.

“I guess it is possible that I would be vulnerable. I have information

on places outside my own system. All the information that I can give

to banks, university, work, and other organizations. Information that I

have outside my control, if these places are compromised my informa-

tion could get stolen. So I remain very careful on the Internet, so far

I have never lost information or been hack to the extent of my knowl-

edge. It could be partly luck because from what I know you can’t be

perfectly safe. Anyone could be targeted and anyone could be hacked”


To provide a representation that can aid in visualizing the distribu-

tion of participants and their level of familiarity of cybersecurity we

plotted a chart of the percentage of users indicating security aware-

ness in relation to their technical proficiency level (See figures 8 and

9). From the data we observed a shift caused by an outlier from the

group of participant with level one in technical knowledge (see figure

8). The outlier was removed and from the following chart (see figure 9).

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Figure 8: Familiarity to Cybersecurity

1 2 3 4 50

20

40

60

80

100

Technical Proficiency

Per

centa

ge

Familiarity to Cybersecurity

Anti VirusTargetedTraining

Figure 9: Adjusted Familiarity to Cybersecurity

1 2 3 4 50

20

40

60

80

100

Technical Proficiency

Per

centa

ge

Anti VirusTargetedTraining

4.4.7 COMPONENTS OF CYBERSECURITY

From the literature we identified three components that make up the

general public perspective on the cybersecurity of electronic devices:

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trust, security, and privacy. For this component of the research we

asked participants to listen to a brief description of what each of the

three components entailed then provide their opinion, and whether they

feel that component is one they relate to or not. A summary of the

results is represented in the figure below (see figure 10).

Figure 10: Cybersecurity component intensity

9A8BTrust8C

13A8BSafety

4C

16A7BPrivacy

2C

0 5 10 15 20Number of Participants

A: High Impact FactorB: Low Impact Factor

C: Circumstance Dependent Factor

In the diagram, each of the three cybersecurity components has three

bars representing the number of participants with similar answers. Each

bar on the chart is labeled “A”, “B”, or “C”. Bars labeled “A” repre-

sent participants who answered that the component was an important

factor that is currently increasing their perceived level of risk. Ones

labeled with “B” illustrate the group of participants who feel that the

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factor does not currently increase their perceived level of risk. The last

portion of the participants indicated the factor was important to them,

but its impact on the level of perceived risk was dependent on the cir-

cumstances or the organization providing the smart home technology.

Those were represented in the diagram with the bars labeled “C”.

For the first component of cybersecurity, trust, participants were

given the following definition. “We define trust as the ability to trust

service providers, and their personal, to do the right thing by you.” 9

of the participants gave answers which indicate that they associate a

high level of risk with the technology and service providers. Remaining

were 8 participants that did not associate a higher level of risk with

the amount of trust they have to service providers, as well as 8 other

participants that where situationally dependent in their responses.

A participant with a view of a positive association between trust of

service providers and cybersecurity had the following to answer.

“I think there is too much monetary benefit for Internet providers

to share information about their clients, for it not to be a concern for

everybody who browses the web. It makes sense as a component of cy-

bersecurity, and one of the main things we should address. Internet and

service providers should be heavily regulated” (participant number 14).

On the other hand a participant had indicated their view of trust for

service providers didn’t relate to them feeling any more or less secure

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when using the services.

“Well if we were to not trust providers then they should all be out

of business by now” (participant number 1).

From the remaining participants one who had indicated the value of

trust as a cybersecurity factor and as an influencing component in their

acceptance of the technology, but had no feelings of insecurity based

on trust in the current circumstances.

“I would say [trust] is definitely a factor. Knowing that someone

has your interest at heart, or thinking that they don’t, goes a long

way whether I would make a purchase or not. Right now I wouldn’t

say I’m distrusting but I’m definitely weary when it comes to Internet

providers” (participant number 2).

The second of the cybersecurity components is safety and can be de-

fined as follows. “If we define safety as relating to the transfer of data

across the Internet, do you perceive unauthorised access to your data

(fraudulent issues and inadvertent) to be likely.” From the sample of

participants, 13 perceived high risk levels from safety, 8 associate low

to no increase in levels of risk, and 4 were situationally dependent.

An interview with one participant provided us with a dose of realism

when they stated the inevitable vulnerability of most technology would

be exploited if the incentive is valuable.

“There are some really smart people in the world looking for oppor-

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tunities like this. With Smart Homes offering so much information,

even if unauthorized access is not possible at first when the technology

is released they would eventually figure it out. So I would err on the

side of caution” (participant number 7).

One participant from the low risk impact portion of the sample in-

dicated their opinion on the associated threat of data safety by stating

that data on the Internet is never safe. See the quote below.

“I guess it is possible that access to the devices is possible, but it is

the Internet and everything can be hacked. So I would sum it up as it

is possible but no more likely that the risks you take when using public

Wi-Fi” (participant number 10).

In the third portion of the sample where participants indicated sit-

uational dependencies one interviewee stated that the risk was present

but its severity was dependent on the precaution of the users, their

answer is given next.

“There is an inherent risk, but it depends. But it depends on how

prepared you are, like you could use a secure connection when you are

browsing the Internet” (participant number 15).

Finally in the third component of cybersecurity, privacy, we gave par-

ticipants the following definition. “If we define privacy as the protection

of personal information so it is not disclosed to or used by others, do

you feel that your privacy is at risk.” Responses were once again coded

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into the three categories, 16 participants had a high level of increase in

predictive risk, 7 indicate low to no increase in risk, and 2 were situa-

tionally dependent.

From the sample a volunteer related privacy with a significant impact

on the level of risk through the highlighting the need to improve security

features in devices to protect the users personal information. A portion

of the interview is given below.

“I do feel that my privacy is at risk. I would prefer if there was a

push to increase the privacy protection on Internet devices rather than

retreating to hiding information, especially when it comes to Smart

Home. That technology will know everything about me, not just the

things I tell it” (participant number 3).

Another one of the participants indicated no impact on risk caused

be privacy concerns as they felt their personal information would not

be sold by the service providers, but rather a generic demographic rep-

resentation of them. The example is given here.

“I feel like a lot of companies distribute or sell your demographic

information, usually for advertising purposes. But I don’t think they

would give away your personal information.” (participant number 18).

One of the remaining two participants who indicated a situational

dependency referred to the different functionality of IoT devices which

could enable access to personal information. Avoiding those particu-

79


lar devices would reduce the risk levels accordingly. The participants

response is given next.

“Well the technology used in Smart Homes is very broad and not ev-

erything stores or transfers personal data, so it would depend on which

technology and devices you are interested in installing I guess” (partic-

ipant number 17).

4.4.8 RANKING THE COMPONENTS BY IMPACT LEV-

ELS

The final part of the interview script aimed to identify which compo-

nents played a more important role in the participants perspective and

identify the relationships between the different factors and the tech-

nology acceptance. From the study sample, one participant indicated

that none of the cybersecurity factors affected their purchasing deci-

sion. That participant had a novice proficiency in technical knowledge,

had a positive predisposition towards installing smart home technol-

ogy and did not associate any security risks from the technology. The

remaining portion of the study sample ranked the three components

in order of personal importance or indicated that all three are equally

important.

Eleven participants would not rank any of the components above

the others. One of the participants explained their reasoning with the

following statement.

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“They are all of the same level of importance, they are like the three

pillars of cybersecurity. You can’t really lose one without losing the

others” (participant number 6).

To give a representation of the resulting responses a table of giv-

ing the cumulative rankings was constructed. Amalgamation of the

rankings on each component where calculated through a logarithmic

weighting system. When a component was ranked of highest impor-

tance (number one) it gains one hundred points, second place gets ten

points, and third place gains one point (Altenbach, 1995). When two

components are given equal ranking, they both receive the same amount

of points given to that rank. The results of the 13 participants’ answers

are represented in the table below (See Table 8).

Table 8: Cybersecurity Component Ranking Amalgamation

Components First place(X100)

Second Place(X10)

Third Place(X1)

Total

Trust 4 6 3 463Safety 6 3 4 634Privacy 3 5 5 355

Note: To calculate the total number of points we awarded: 3 points for each first placeranking, 2 points for second place and 1 point for thirst place.e.g., Total point calculation for Trust; (100 points X 4) + (10 points X 6) + (1 point X 3)= 463 points

It is important to recognize here that the numbers given in the ta-

ble above are a a visualization of the answers through interpretation

of the results. Altenbach (1995) mentions that the conversion of these

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qualitative answers into a numerical data is an aid to allow the analysis

to take shape and does note represent a quantifiable measure of the

importance each component has over the other.

For each of the components we have pulled out an example of a par-

ticipant that ranked the component at the top rank, to give an idea of

their reasoning and thoughts.

For the trust component a participant argues that a lack of trust in

providers will inherently reduce the user’s ability to believe in strong

safety and privacy practices regardless of actual precautions. See details

below

“Safety and privacy don’t mean anything if you don’t trust the peo-

ple in charge of them to be doing their utmost best. Trust would be the

most important, to me. The next would be privacy, so that informa-

tion I don’t want shared with others wouldn’t be shared with others.

Any information that I share with anyone involved in the security of

said information, is information that I’m already willing to share, and

so don’t entirely mind having it be made known to someone I might

not have intended for it to be shared with. The last would be safety,

because in my opinion, it’s the most vulnerable if the other two are

taken care of, and so it’s the one I could defend myself against with

the most confidence. Don’t offer any information that I don’t want

intercepted. If I can trust the service providers, and ensure that my

privacy is protected, then the safety of any other information isn’t my

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highest priority. Besides, if I trust my service provider to do their best,

then they’ll work hard to make sure the security is protected, so there’s

that” (participant number 7).

The argument from another participant was that Safety played a

more important role, where they could ensure their private and personal

information could be kept secure by taking actions themselves to do so.

However, the role of the company to do their job as well as protecting

its clients creates the safer environment in which this participant would

be willing to partake. A portion of the interview is given next.

“Safety is at the top, followed by trust, and then privacy. With my

knowledge I can protect myself and the information that is important

to me. I want to know the company has done their job and gone above

and beyond to ensure the safety and security of my information on their

end” (participant number 11).

A response from one of the interviewees to the priority of each of the

cybersecurity components highlighted the importance of privacy above

the other two components for one simple reason. That reason is that

you can not change your identity. While cyber attacks on technology

can cause monetary loses, identify theft and extortion are very serious

risks that could be caused by the high level of invasion to privacy in

this scenario. The response is shown below.

“Privacy and personal information is the most important thing in

my eyes. I want to be able to know that my personal information is

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safe, especially with the risk of identity theft and everything. If you

put your trust into the providers and they break it, its gonna be very

bad for you. So privacy is first, trust and safety are equally important

but come in second” (participant number 15).

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5 DISCUSSION

This chapter will talk about the findings of the study and what they

might mean. We will examine how the findings can address the research

question and the theories the explain them. The chapter is organized

into six sections: (1) summary of results, (2) interpretation of results,

(3) comparison to the literature, (4) implication of findings, (5) limita-

tions, and (6) recommendations for future research.

5.1 SUMMARY OF RESULTS

In the summary section we will be revisiting the research question and

propositions from the literature review, then going through the key pat-

terns of findings from the results section highlighting the significance

they hold.

As mentioned throughout this thesis, the research question focuses

on examining the role cybersecurity plays in smart home technology

adoption. This research question is formed from a literature gap which

lacks the presence of a combination between research of cybersecurity

challenges in the future of smart home technology and the technology

acceptance and adoption theories.

From our research, we have identified three main propositions to ex-

plore. (1) Cybersecurity is a factor in the technology adoption model

85


which affects the acceptance of smart home technology. (2) Cybersecu-

rity would be observed by the average consumer as components made

out of the perceived areas of risk. (3) The components of cybersecurity

are: trust, safety, and privacy.

From the results of our interviews, we observed in the identification

of what smart home technologies mean to the participants, that there

are significant variations and inconsistencies amongst definitions. The

participants gave indication of the technology which would classify as

part of the smart home technology umbrella but generally could not

define what makes this technology suitable to be called smart home

technology.

We could deduct from the interviews that some had formulated an

opinion about smart and connected technologies from advertisements

of one or two companies over media. That has caused the definition in

consumers’ minds to fall behind the literature where the definition still

relates to a specific technology rather than the more accepted relation

to the behavioral focus of the technology with the users’ needs. Using

a technology focus over a behavioral focus leads to a reduced ability in

categorizing whether a particular device fits into the definition suggest-

ing that the behavior of consumer would follow suit of the literature.

This could be expected to show in observation of largely inconsistent

arrays of definitions which get consolidated over time with standard

practices emerging as use of the term and the technology become more

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common and main stream.

Moving onto the intent to purchase questions, a key observation is

made in the different levels of risk concerns by participants based on

their technical proficiency. As we examine the answers of our volun-

teers, we notice the distinction of answers from highly proficient to

novice technology users. Users with a higher rating of technical profi-

ciency displayed concerns for security risks associated with the devices,

often this group of participants identified one or more of the cyberse-

curity components directly while discussing their intent to purchase.

Those concerns didn’t always cause the user to lose interest in purchas-

ing, but they were consciously aware of their existence. But on the

other hand when consumers had a lower level of technical skill, their

intent to purchase had no mention of security risk, but appeared to be

related to other factors, such as costs or convenience.

The next key observation made builds on the evolution of the adop-

tion model. The discussion of key factors and concerns with the par-

ticipants revealed this information. Early in chapter 2 we introduced

the UTAUT2 Model and stated the definitions of the determinants for

user behavior. Later in that chapter, we used the literature to add

cybersecurity as a determinant in our preliminary theoretical model

with three components that make up cybersecurity. Those factors were

safety, trust, and privacy. From the results of our interviews, we col-

lected 14 different factors as identified by the users. Some of those

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factor can be mapped directly to the UTAUT2 model and the prelimi-

nary theoretical model.

We demonstrate here how the user identified factor for adoption

can be grouped under the determinants for the theoretical model. For

each of the determinants Venkatesh et al. (2012) gave definitions and

grouped smaller factors from other literature which fit the definition

to increase the significance for each determinant. We will group our

factors into the given definitions as well. The first given determinant,

performance expectancy has a definition where three of the user de-

fined factor fall under (numbers 1, 5, and 11) those are: performance

and convenience benefits, time and energy saving, and accessibility.

Effort expectancy can capture both the learning curve and the retrofit

factors from our list (numbers 8 and 14). Social benefit is given by the

identified lack of social norm (number 7), and price value by value of

the technology (number 9). The last UTAUT2 determinant, facilitat-

ing conditions, is broadly defined and can be related to four of the user

identified factors (numbers 3, 4, 10, and 13): installation and operation

costs, living space restrictions, closed software, and reliance and relia-

bility.

The additional determinant which we identify in this research, cy-

bersecurity and its three components are captured by security risks,

lack of trust, and lack of privacy (numbers 2, 6, and 12). Therefore we

can construct the full preliminary theoretical model directly from the

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answers provided by the interviewee sample. It is important to note

that the grouping of the user identified factors into the determinants is

based on the definitions of the determinants as given by research.

Smart home technology operates under many sectors and indus-

tries, the literature mentions home automation, entertainment, security,

healthcare, remote access control, and energy efficiency to name a few.

Out of those sectors, healthcare is the most dominant in research with

a larger portion of journals dedicated to the subject and predictions

of its future potential market value growing faster than all the other

sectors. With that, it is important to make the observation of the data

showing healthcare as the least pressing use of smart home technology

in the consumers persxpective. When asked about the benefits and use

of smart home technology, the users prioritized home automation the

most and only gave one mention of healthcare placing it as the least

important sector.

The cybersecurity section of our interview began with a series of

questions to identify the user’s perception of risk levels. There were

three risk levels used, here they are given in order from highest risk

perception to lowest: training in cybersecurity, potential information

theft target, and basic precautionary protection software.

A trend is observed when the participant answers where represented

in a graph based on their level of technical proficiency (see figures 8 and

89


9). The trend indicated a positive relationship between technical profi-

ciency and risk perception. As we look at the data, we notice that with

participants who had a lower level of technical knowledge the percent-

age of responses indicating perceived risk at each of the indicators we

slow. Compared to the highly technical participants of whom a larger

portion responded in a manner that indicates strong perception of risk.

Following familiarity to cybersecurity, the section moves into examin-

ing the components which define cybersecurity in the minds of the con-

sumers. The literature supported three key components: trust, safety,

and privacy. The data from our participants indicates the presence of

a relationship between the component, and cybersecurity as a factor in

adoption. All three of the components from the literature had answers

indicating more participants make the connection to cybersecurity. We

observe that privacy had the highest amount of agreement and largest

impact on feeling secure, with 16 of the participants listing it as an

important factor. Safety was second in order of importance followed

by trust in third. It is important to note that this is the order of risk

impact and not the order of personal value to each of the components.

The graph of cybersecurity component intensity (see figure 10) visu-

alizes the ratio of participants who feel the component is high risk, no

risk, or is dependent on the circumstances. Those three groupings were

labeled “A”, “B”, and “C” respectively. An observation made clearer

through the visualization of the data, as we move down the graph from

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the trust component through safety and to privacy. While bar A grows,

bar B keeps its size only being reduced by one participant when we get

to privacy. The growth of bar A is causing a reduction in participants

in bar C. Hence we interpret this observation by considering that fol-

lowing scenario; the strength of a cybersecurity component’s risk sways

over consumers from being undetermined to feeling that the component

is high-risk value.

Ranking the components of cybersecurity in order by impact level

is the last final part of the interview and in it observe the how the

consumers chose their priority for cybersecurity focus. The table at the

end of chapter four gives us an overall numerical total to identify the

ranking of each component. (see Table 8). The order of importance as

indicated by the ranking system is as follows: safety, trust, and privacy.

The observation here is that this ranking does not line up with the data

from the component risk intensity ranking, however it does match the

ranking from the earlier key factors and concerns section.

5.2 INTERPRETATION OF FINDINGS

In this section, we will go through the key findings from the section

above and discuss their meaning, provide what knowledge claims can

be made from them, indicate how they relate to our propositions and re-

search questions, and indicate any unexpected findings that have come

91


up.

We begin with the users’ lack of a consistent definition of smart

homes. To the extent of current research on the topic of smart homes,

a standard definition is still being worked on, and the majority of con-

sumers can only derive their definitions from its portrayal in the media

. In two major ad campaigns, by Samsung and Nest Labs, we observe

the companies instructing the consumers on how and why they should

use smart home devices (Charara, 2015; Torres, 2016). The ads create

an impression in the consumers’ minds of what smart homes are based

on the instructions of those campaigns. Those definitions could cause

consumers to be confused as to which products are “smart” products

and which are not.

Another area of difference between consumers and research is the pri-

ority of industry sectors under smart home technology. The literature

suggests the largest sector to be healthcare with the Baby Boomers

generation approaching and beginning their 70s and beginning to rely

more on healthcare to keep to a normal level of daily functionality.

These are some of the journals which indicate a focus on healthcare

as main use of smart homes (Warren et al., 1999; Penaud et al., 2004;

Demiris & Hensel, 2008; Chan et al., 2009; Ziefle et al., 2011; Alam et

al., 2012; Ni, Garcıa Hernando, & de la Cruz, 2015). From our findings,

the participants did not prioritise the use of smart home technology in

the healthcare system, but focused more on home automation and en-

92


ergy efficiency.

Participants indicated which facilitating conditions they felt influ-

enced their intent to purchase smart home technology. The observations

made in that section supported the findings from the literature where

factors were given to fit under each of the existing determinants from

the UTAUT2 model. Additionally, the observations gave evidence that

supports our first and third propositions. Amongst the factors identi-

fied by the participants in the section were trust, safety, and privacy.

Those give supporting evidence to the existence of cybersecurity as a

determinant of behavioral intent, as well as the main components of

cybersecurity being the three factors mentioned.

The second proposition identified in our research is supported in the

observations made through the cybersecurity component intensity sec-

tion. The section examined the consumers’ perception of risk for the

three main components of cybersecurity. The literature identifies a re-

lationship between risk perception and the consumer decision making

process (Stampfl, 1978; Kim, Ferrin, & Rao, 2008). Respondents indi-

cated that all three of the components exhibited some level of associated

risk, which answers are question of whether cybersecurity is observed

by consumers as components of perceived risk.

From the key observations, we note a few that do not relate to our

propositions but provide some additional valuable insight into our re-

93


search question. These observations come from the intent to purchase

and familiarity to cybersecurity sections, where a trend is observed

that indicates a relationship between technical proficiency and level of

perceived risk from cybersecurity. The relation indicates an increase

in consumers’ tendency to be more cautious and aware of the risks

associated with the smart home systems when their level of skill and

knowledge of technology was higher.

Reflecting on this observation we find theoretical support in research

for a relationship between technical knowledge and cybersecurity. In

examining the political dynamic core of cybersecurity and development

of theoretical framework of the future development of cybersecurity

Hansen & Nissenbaum (2009) gave reasoning for such a relationship.

Their study reviled that at the rate of technological development and

evolution of cyber-attack methods emphasized mastery of the field and

expert knowledge to hold the privilege of being the speaking authority

on such a topic. Reports for public safety strategies also emphasized

the need for highly technical and capable individuals to be present in

leading roles at every level of government operation to ensure the cor-

rect skills are available to defend against the threats of cyber-attacks

(Evans & Reeder, 2010).

This observation changes the dynamic of the relationship proposed

between cybersecurity and behavioral intent. With this additional ob-

servation, we could propose the relationship to be as follows; cyber-

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security is determined by three main components - trust, safety, and

privacy - that are moderated by the consumers’ technical knowledge.

Additionally, the observations reflect another knowledge claim that

can be made of the three components of cybersecurity. From both

the cybersecurity component intensity and the ranking of components

section we can identify the strengths of each component. The two

rankings measure different values, component intensity ranks the com-

ponents based on the severity of risk, while the priority ranking orders

them based on consumers’ need for security assurance.

Finally, we arrive at our research question. What role does cybersecu-

rity play in smart home technology adoption. Based on the observations

made above, and the data in this research, we find that cybersecurity

is a determinant of behavioral intent which has three main components

- trust, safety, and privacy - that are moderated by the consumers’

technical knowledge. We represent this new understanding in a revised

model which includes the effects of technical knowledge (see figure 11).

The model represented in the figure above (see figure 11) visualizes

the expected relationship between all the factors of adoption. As we

have mentioned earlier, we do not set out to disprove the UTAUT2

model and although some of the labels and relationships are not shown

that is for the purpose of simplification not elimination.

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Figure 11: Revised Theoretical Model: Smart Home Technology Ac-ceptance

Our contribution to the model is represented within the cybersecurity

label and its relationship to the rest of the model. Cybersecurity is a

determinant of behavioral intent an has a similar relationship to behav-

ioral intent as those of determinants in earlier models (e.g., performance

expectancy or social influence). We provide to following definition for

the cybersecurity determinant; Cybersecurity is the organization and

preparation of protective resources which provide the users with se-

curity in end-to-end operation of the technology which reflect on the

consumers’ perception of their trust, safety, and privacy. This defini-

tion is developed from the collection of examined literature along with

the results of this study.

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Within the cybersecurity label we find its three main components,

trust, safety, and privacy as well as their moderator, technical knowl-

edge. The three components of cybersecurity are all interlinked as

we suggest their relationship to be codependent. From our observa-

tion the participants who stated that one of the components were of

high importance to them also indicated a higher overall risk affecting

their behavioral intent. That suggests a relationship where any of the

components being present increases the overall perceived risk of cyber-

security. The technical knowledge connects to the three cybersecurity

components as it relates their intensity and likelihood of their presence.

5.3 IMPLICATIONS TO THEORY

Our findings reflect consumers’ perception of smart home technology

providing valuable insight into the minds of users. This insight allows

for the expansion of our understanding of consumer behavior, further-

ing the development of theoretical frameworks and models for the study

of technology adoption patterns.

The developed models such as UTAUT2 can utilize our findings

through the development quantitative and empirical studies that test

the propositions brought forth through our exploratory research by

adding statistically significant determinants of behavioral intent and

increasing the accuracy of the adoption models. The value of such

97


exploratory research to the current technology adoption models are

present and can be observed in the likes of research by Zeithaml (1988)

and Meyers-Levy & Maheswaran (1991) which were later cited by Venkatesh

et al. (2012) for the development of the UTAUT2.

Along with the determinants we suggest to use in expanding the

adoption models we observed findings that have implications on the

models as a whole. The perceptions and definitions of smart home

technology products given by the consumers was influenced by adver-

tising campaigns in the media. Consumers’ understanding of what the

products are affect all the determinants included in the adoption mod-

els. If a consumer perception of smart homes is inaccurate and limited,

then their performance expectancy and price value would be inaccu-

rate. The effects of consumer knowledge are not currently accounted

for by the UTAUT2 model.

Adaptation of these findings into future research on technology adop-

tion would provide additional value and improve the contribution to

theoretical models. Consumer perception of emerging technology can

have critical implications onto the future development of the field.

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5.4 IMPLICATIONS TO PRACTITONERS

One of the key observations of our study indicates that cybersecurity

does have an impact when it comes to smart home technology accep-

tance. These findings could prove to be valuable for organizations and

practitioners in the smart home industries as well as others marketing

IoT devices towards individual consumers in settings that are similar

to those of smart home markets.

Entrepreneurs and managers using the model to anticipate the adop-

tion of smart home technology would allow them to gear their products

towards the right market and audience when designing and marketing

its key features. Hence, a company might choose to market to a low

technical demographic and emphasize the low effort expectancy of their

technology without worrying about its cybersecurity. Alternatively, if

they decide to target a more technologically skilled demographic they

could indicate their cybersecurity by emphasizing one or more of the

three main components of cybersecurity.

The three components of cybersecurity could be utilized as differen-

tiators between competitors or as value propositions which could result

in a competitive advantage. Each component would provide potential

for research and development allowing companies to develop products

centered around cybersecurity.

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For academics and the educational system, the implications of our

findings give reason to improve the mandate of studying cybersecurity

as we expect to have a higher demand for cybersecurity experts with

the growth of the IoT industry.

Developers of connected devices would be able to use information

from our theoretical model to identify the critical areas of focus in their

software. It is important for developers to understand their users and

how they intend to interact with the technology to be able to reduce the

barrier of human computer interaction. Improving the consumer expe-

rience through enhancing features valued by the user increases tech-

nologies changes of success and reduces the costs of support.

The development of adoption models that utilize user perspective to

define determinants across the model helps move companies towards

a user-centric design. When organizations utilize user-centric devel-

opment strategies, both the organization and the consumers benefit

(Hoyer et al., 2010). The implications of focusing on improving the

cybersecurity of smart home technologies would benefit the companies

bottom line, but also increase the security of the technology users.

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5.5 LIMITATIONS

Through our research, we have aimed to maintain an unbiased collec-

tion and interpretation of our data. However, limitations in research

are unavoidable. This section will list the limitations of our research to

the best of our capabilities.

At the beginning of our research we introduce some definitions that

are used to identify key terms used throughout the article. We took to

the literature in our process of identifying the most appropriate defi-

nitions for cybersecurity, smart homes, and other critical terms. The

selection of those definitions restricts and limits the scope of research.

If different definitions were used, this research might have arrived at

different results.

The research examines cybersecurity of smart home devices with

potential consumer, most of whom have never owned this type of con-

nected technology before. The implication of security risks in a cyber-

physical system are higher than those from devices that do not control

physical objects. A possible limitation comes from the participants in-

ability to perceive the severity of these risk implications without prior

experience.

During the literature review process challenges were identified for

the future of smart home technology other than cybersecurity. How-

101


ever those challenges, such as human interaction and social barriers,

were not included in the interview structure. This could have limited

the exploration of available data on acceptance and adoption of the

technology.

Qualitative research in its nature faces a large challenge in its con-

duct to maintain objectivity and reliability. Although the qualitative

research method was selected to avoid limiting participant responses,

the mixed method approach would have allowed for benefits from both

qualitative and quantitative methods (Creswell, 2013).

The sample of participants was drawn from the location of our re-

search (the city of Ottawa), and the majority of our participants are

residents of this city. For the sample to be representative of the coun-

try as a whole, the data must be drawn from a larger pool and with a

larger sample size. Our sample also contained a fairly large concentra-

tion of younger participants, there are a number of factors that could

have caused this. This is likely due to the nature of the topic of study

relating to technology. This may have resulted in a portion of potential

participants, generally older population, avoiding taking part in the

questionnaire if they have lower technical knowledge. Additionally the

qualifying criteria for participants required respondents to be looking

to purchase a home or have done so within the past year. With those

factors, access to older age groups was difficult. The lack of partici-

pants over the age of 39 implies that our results are not generalizable

102


to older generations.

5.6 FUTURE RESEARCH

We suggest that future work could be done to further this area of re-

search through addressing the limitations in our research. As the lit-

erature moves towards an accepted standard for definitions, the scope

of research should adapt with it to develop an inclusive adoption model.

The lack of adopted standard definitions by the general public for

many of the terms used throughout this study has a large impact on

the outcome of the study. We believe the results are dependent on our

choices of definitions, a different outcome might be reached with other

definitions. As a more standardized definition emerges new research

using the standard definitions would provide valuable information for

this field.

We identified factors that could influence consumer behavioral in-

tent from the literature review that do not relate to cybersecurity (i.e.,

human-computer interaction and social barriers to adoption). Those

factors did not meet the scope of our research. Future research could

examen those factors for their relation to consumer behavioral intent

to purchase and expand on the adoption model.

Our qualitative exploration of the data provided valuable informa-

103


tion on the relationships proposed by consumers; however, validation

of those relationships with numerical data was not presented by our

research. As the market for this technology becomes more well under-

stood, and with larger study samples, other research methods can be

used to improve on the findings. We suggest the in future research

conduct of the mixed method approach could by used to provide more

statistical support of the relationships identified in our research.

The demographies of our study sample are limiting and do not in-

clude older age groups. Studies can be conducted in different geographic

locations and would be valuable in introducing new findings that would

affect the theoretical model. Studies that investigate the perception of

the elderly on the subject would significantly improve the model’s ca-

pability to explain the behavior of consumers of that age group.

We explore the role cybersecurity plays in the acceptance and adop-

tion of technology, yet we have not provided any solutions to mitigate

the risks associated with it. More research in needed in the field of

cybersecurity to help in the protection of our future.

104


6 CONCLUSION

Lack of predictability in the behavior of new smart home technology

products in the markets lead to the need for research identifying and

improving the factors determining consumer acceptance and adoption.

The literature examines the extent of research available on adoption

model, the boundaries and definitions of smart homes, and the future

cybersecurity challenges.

This research conducts exploratory examination of the consumer be-

havior and uses semi-structured interviews to collect its data. The

research methodology guides the development and conduct of the re-

search to minimize bias and assure adherence to the ethical guidelines.

The results were transcribed from a final count of 25 participants

from 34 initially interested in participating. Following a five stage

modified grounded theory approach, the results were organized to give a

clear representation of the collective responses. Observations were high-

lighted for further interpretation. Development of connections between

observations revealed the key patterns which were used to identify the

relationships and determinants in the adoption models.

Our findings introduce the determinant of cybersecurity to the UTAUT2

model with three components and a moderating factor. Trust, safety,

and privacy are the components of cybersecurity moderated by the

105


consumers’ technical knowledge. We discuss the implication of those

findings as well as their limitations. From there we identify suggestions

for future research that could improve the adoption models of smart

home technology.

Cybersecurity is often overlooked, but observations suggest it is rapidly

becoming a critical factor in our technology. Developers and manufac-

turers of smart home technology should work together towards making

cybersecurity a clear priority which we value in our homes and our

technology.

106


7 APPENDICES

7.1 APPENDIX A - INTERVIEW SCRIPT

Knowledge questions

Q1: Have you heard about smart homes before or have you been

made aware of the Internet of things technology?

Q2: How would you describe your level of technical knowledge?

Q3: Could you provide some examples of the way you regularly in-

teract with technology?

Q4: What are some of the challenges you encounter when working

with technology?

Q5: In your own words, how do you define smart homes?

Aim: understand the depth of knowledge participants have towards

smart homes.

Q6: This study adopts a definition of smart homes by Frances K.

Aldrich (2003), After I read this definition to you, could you indicate

how this definition reflects on your understanding on what you believe

are smart homes?

Quote: “A ‘smart home’ can be defined as a residence equipped with

computing and information technology which anticipates and responds

to the needs of the occupants, working to promote their comfort, con-

venience, security, and entertainment through the management of tech-

nology within the home and connections to the world beyond” (Aldrich,

2003).

107


Q7: What stood out for you from the definition we gave of smart

homes?

Aim: provides a common understanding of the key meaning of smart

homes and what it means to the participants.

Q8: Have you used smart technology before? How was your experi-

ence with the technology?

Q9: Do you currently own a house, or are in the process of purchasing

a house? (if you don’t own a house, what are the key features that would

appeal to you in your future home?)

Q10: Do you currently have smart home technology at your living

area? How do you use the smart home technology you have?

Q11: Would you currently be inclined to install smart home technol-

ogy in your residence? Could you tell me why you would buy?

Aim: provides indicators of the participants predisposition and will-

ingness to own smart home technology.

Q12: What factors influence your decision about smart homes?

Q13: If a house was equipped with Smart Home technology, how

would the value of that house change in your opinion?

Aim: Identifying the key factors the participant uses to make the

purchasing decision and adoption of smart homes.

Q14: How would you expect living in a smart home could affect you

day to day life?

Q15: In terms of personal changes to your day-to-day activities, what

benefits can using smart homes provide for you?

Aim: find the technology services that participants value when con-

108


sidering an investment in smart homes.

Cybersecurity Questions

Q16: What level of training are you subject to in maintain the secu-

rity of your software and hardware?

Q17: What level of security precaution (run and updating anti-virus

software, firewall, suspicious of emails from unknown sources, using

secure password, updating passwords) do you take no regular basis?

Q18: With the large number of reported cyber attacks reported lately

in the media, do you feel your information is targeted?

Aim: identify the level of cybersecurity the participants are familiar

with when using regular daily technology

Q19: What does cybersecurity mean to you?

Q20: We have identified three components of cybersecurity (trust,

safety, and privacy). We read to you a brief description for each com-

ponent then ask you to provide your opinion, and whether you feel

that component is related to cybersecurity and affecting your intent to

purchase.

Trust - We define trust as the ability to trust the service providers

and their personal to “do the right thing by you”.

Safety - We define safety as relating to the transfer of data across

the internet, do you think unauthorised access to your data (fraudulent

issues and inadvertent) is likely?

Privacy - We define privacy as the protection of personal information

so it is not disclosed to or used by others, do you feel that your privacy

109


is at risk?

Aim: Determine the relevance of the cybersecurity components to

the participant’s view of cybersecurity.

Q21: how would you rank the three components we identified earlier

(trust, safety, and privacy) in terms of importance?

Aim: Find the level of importance each component plays.

Q22: Do you have any further questions?

110


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